Jobs ML / AI

We are looking for a hands-on engineer who can deploy AI/computer vision solutions into real-world manufacturing environments and work directly with customer infrastructure, factory systems, and operations teams.
This is not a pure backend or ML research role.

The client is building AI-powered computer vision and predictive systems for manufacturing companies.

The position combines AI systems, industrial infrastructure, edge deployments, networking, and customer-facing integration work.
You will own the full deployment lifecycle — from technical discovery and integration to production rollout, troubleshooting, and long-term handover.
 

Responsibilities

• Deploy AI/computer vision systems into live manufacturing environments
• Integrate AI systems with factory infrastructure, OT/IT systems, and customer cloud platforms
• Work with industrial protocols and factory systems (OPC-UA, Modbus, PLCs)
• Configure and support edge AI infrastructure, including NVIDIA Jetson devices and industrial vision systems
• Build and improve edge-to-cloud data pipelines
• Troubleshoot software, networking, and production integration issues
• Work directly with customer IT, operations, and engineering teams
• Document deployment architecture and create handover materials
• Support customer onboarding, training, and adoption
• Participate in technical discovery and pre-sales discussions
   

Requirements

Must Have

• 6+ years of overall technical/engineering experience
• 3+ years of production Python development experience
• 3+ years of hands-on Linux and Docker experience in production environments
• 3+ years of experience with production deployments, infrastructure integrations, or system integration projects
• Understanding of networking fundamentals for production environments (TCP/IP, VLANs, firewalls)
• 2+ years of customer-facing engineering experience working directly with external stakeholders
• Professional English communication skills

Nice to Have

• 2+ years of experience with industrial automation or manufacturing systems
• 1–2+ years of experience with OPC-UA, Modbus, PLC systems, or industrial networking
• 1–2+ years of experience with computer vision or Edge AI systems
• Experience with NVIDIA Jetson or similar edge AI platforms
• Experience with cloud platforms (AWS, Azure, or GCP)
• Understanding of OT/IT infrastructure and factory environments
   

We Offer

• Time Off: 20 paid vacation days and 5 paid sick leaves per year.
• Growth: Personalized development plan (PDP) and training compensation.
• Perks: Сourse compensations and work equipment (laptop/monitor).
• Support: Full accounting support.

We’re building something very different at PRAI.

This is not a typical job.

This is a chance to work at the edge of AI, media, and attention economy.

About PRAI

PRAI is an AI platform transforming PR and communications.

We’re building AI Employees — systems that:

• generate content

• run outreach

• replace slow, manual work

Now we’re scaling into AI video content — fast, viral, performance-driven.

If you understand where media is going — you’ll get it.

What you’ll do

• Create viral short-form videos (TikTok / Reels / Shorts)

• Use AI tools:

• Sora (or similar)

• Runway / Pika / Kling

• Build clickbait hooks (first 1–3 seconds = everything)

• Turn ideas into high-converting video flows

• Produce content daily (speed matters more than perfection)

• Test → iterate → scale what works

Work format

• Fully remote

• Full-time

• Startup speed (fast, intense, no hand-holding)

• Performance-driven environment

We use Hubstaff for time tracking — we’re focused on output and accountability.

Who we’re looking for

You’re not “just editing videos”.

You:

• understand attention and psychology

• know what makes content go viral

• can produce a lot, not just “perfect”

• move fast and don’t overthink

Mindset

• speed > perfection

• execution > talking

• no excuses, just results

• test aggressively, drop what doesn’t work

Test task

We may ask you to create:

3 short AI-generated videos

→ strong hook

→ clear flow

→ engagement-focused

Why people want to work with us

• You work with cutting-edge AI tools before most people even understand them

• You build real output, not fake busy work

• You move fast and actually see results

• You’re not stuck in corporate nonsense — only execution matters

• If you’re good, you grow very fast with us

In one sentence

We’re building AI-driven content that people can’t scroll past.

APPLY IF:

You feel this is your environment.

Company website:
prai.us

We’re looking for an AI Engineer to join our outsourcing team — not a pure ML researcher, but a pragmatic, data-driven backend engineer who knows how to put LLMs, vision APIs, and off-the-shelf models to work inside real products.

Most of our work isn’t training models from scratch — it’s understanding the business logic, collecting and cleaning data, wiring it into LLMs or services like AWS Textract, and shipping the result as a reliable API inside our existing platform.

If you’ve spent the last few years building APIs and integrations, you’re comfortable with data, and you’ve leaned hard into Cursor or Claude Code to deliver projects faster — this is for you.

What you’ll do

• Build and ship LLM-powered features: prompt design, data prep, passing context to the model, parsing and validating output, returning clean APIs.
• Design and implement integrations between our product and third-party AI services (OpenAI, Anthropic, Hugging Face models, AWS Textract, etc.).
• Take document-processing and computer-vision tasks end-to-end: ingest → Textract/vision API → post-process → structured output consumed by our backend.
• Write backend services and APIs in Node.js (our primary backend), dropping into Python when a task calls for it (model work, data scripts, fine-tuning).
• Fine-tune existing models and prompts — not from scratch, but iterating on what’s already in place to get better accuracy, cost, or latency.
• Do the unglamorous but critical work: data collection, cleaning, transformation, pattern-finding — often by letting an LLM do the heavy lifting on structured and unstructured input.
• Maintain and improve existing AI and automation workflows already running in production.
• Monitor cost and performance of model/API usage, propose optimizations, and forecast costs for new features.
• Prepare and present demos and solution overviews to U.S.-based clients.
• Document architecture, prompts, and pipelines in Confluence.

What we’re looking for

• 2+ years shipping production backend systems, with meaningful hands-on experience integrating LLMs or AI APIs into real products.
• Strong in Node.js with the flexibility to work in Python — or a Python engineer who’s comfortable committing Node.js code. We need someone fluent on both sides; pure-Python candidates won’t be a fit.
• Solid grasp of algorithms and data structures — enough to write custom logic when an LLM or library can’t cover the case.
• Real experience with LLM integrations: OpenAI, Anthropic, or similar. Prompt engineering, function/tool calling, structured output, retrieval, evaluation.
• Familiarity with the Hugging Face ecosystem — picking models, running inference, fine-tuning where it makes sense.
• API and integrations background: REST, auth, webhooks, rate limits, retries, idempotency — the stuff that makes integrations not break at 2 a.m.
• Comfortable with data work: collecting, cleaning, transforming, and analyzing data (SQL, pandas, or the Node equivalents).
• Working knowledge of AWS — especially Textract, Lambda, S3, and the services around document and data pipelines. Bonus for Athena, Glue, Kinesis, SageMaker.
• Exposure to NLP and Computer Vision concepts — enough to pick the right tool and evaluate results, not necessarily to train SOTA models.
• Familiarity with CI/CD and deploying AI-powered services to production.
• Experience building chatbot workflows — conversational flows, multi-turn logic, context management — is a plus, as this is among our planned projects.
• AI-native delivery workflow. You use Cursor or Claude Code daily and know how to ship a project with minimal hand-written code — scoping work for the agent, reviewing generated code critically, orchestrating multi-step tasks, and getting to shipped quality faster than a traditional workflow. If you can’t describe how you use these tools to deliver, this role isn’t the right fit.

Nice to have

• Experience fine-tuning open-source LLMs or vision models on domain-specific data.
• Background in fintech, healthcare, or construction domains.
• Experience with vector databases, RAG pipelines, or agentic workflows.

What we offer

• Competitive salary with regular reviews.
• Support for individual entrepreneurs with accounting assistance.
• Fully remote work.
• A clear path for professional development and growth.
• A friendly team environment and engaging team-building activities (online and offline).

Senior AI Engineer
An AI consulting group that builds serious, production-grade systems for companies ready to operationalize artificial intelligence across their business. We do not build gimmicks. The main focus is on custom AI solutions that integrate directly into operations and drive measurable results.
 

We’re looking for a Senior AI Engineer for one of our clients  - an AI consulting group that builds production-grade systems for companies ready to operationalize artificial intelligence across their business. This is a hands-on role for someone who doesn’t just experiment with AI, but has built, deployed, and optimized real AI systems in complex, production environments.

This role is for someone who takes full ownership of AI systems - from architecture to performance. You’ll work at the intersection of LLMs, distributed data processing, and backend systems, building scalable AI pipelines and knowledge systems in a high-impact environment where performance, reliability, and flexibility (including airgapped deployments) matter.

Your responsibilities will include:

• Design and build distributed data pipelines (Apache Beam, Python) for large-scale document and model processing;
• Implement horizontally scalable LLM-powered extraction workflows across thousands of entities;
• Build runner-agnostic pipelines that run across multiple environments (local, cloud, on-prem);
• Design and implement entity resolution and cross-referencing systems with confidence scoring;
  Architect and build graph-based Knowledge Bases (Dgraph or similar), including schema design and query optimization;
• Develop pluggable LLM extractor frameworks (classification, relationships, completeness, document linking);
• Build abstraction layers for LLM providers (Anthropic Claude, Google Gemini, local models via Ollama/vLLM);
• Optimize LLM usage for cost, latency, and reliability in production environments;
• Design and implement backend service layers (Go-based APIs) connecting AI pipelines with agent systems;
• Ensure observability, debugging, and performance monitoring across distributed AI systems;
• Package and deploy systems using Docker (docker-compose, containerized environments);
• Collaborate directly with client teams on integrations, validation, and production rollout.

What we expect from you:

• 5–8+ years of experience in AI Engineering, Data Engineering, or Applied ML Infrastructure;
• Expert-level Python;
• Strong experience with distributed processing frameworks (Apache Beam preferred; Spark/Flink acceptable);
• Hands-on experience integrating LLMs in production (prompting, orchestration, provider abstraction);
• Experience with graph databases (Dgraph, Neo4j, JanusGraph, or similar);
• Strong understanding of distributed systems, parallel processing, and large-scale data pipelines;
• Solid SQL and data modeling fundamentals;
• Experience with Docker and containerized deployments;
• Experience with cloud platforms (GCP preferred, AWS/Azure acceptable);
• Strong backend/system design mindset (performance, scalability, reliability);
• Ability to work independently and take ownership without micromanagement;
• Strong problem-solving skills in complex, ambiguous environments;
• English level: B2+ (C1 preferred);
• Availability to overlap with US business hours.

Our Customer offers:
- Four-month full-time contract engagement;

- Remote work with overlap in US business hours;

- High-impact project with direct influence on production AI systems;

- Close collaboration with client’s product and engineering teams;

- Opportunity to build core infrastructure for real-world AI applications — not prototypes.

About us

Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/

About the role

At RubyLabs, we’re seeking a senior AI Engineer (Node.js / Next.js / TypeScript) to shape our AI infrastructure and drive production-ready LLM experiences. You’ll work in a modern stack, making data-driven decisions around model performance, reliability, and cost.

You’ll own advanced prompt systems, structured outputs, and complex LLM workflows using LangChain or LlamaIndex. Observability, debugging, and evaluation are core to the role, leveraging Langfuse and AI gateways like OpenRouter to continuously improve model quality and operational efficiency. You’ll take full ownership of key AI features from experimentation to live production.

Key Responsibilities

• Advanced Prompt Engineering: Designing complex, dynamic prompt templates with conditional logic and efficiently reusing information and context within prompts to maximize generation quality and reasoning.
• Structured Outputs & Schemas: Implementing various response schemes (JSON mode, function calling, Zod/JSON schemas) to ensure AI outputs are predictable and ready for seamless integration into application logic.
• Prompt Engineering & Evaluations: Building robust evaluation pipelines and using Langfuse to collect feedback and score the quality of responses in real time.
• Tracing & Debugging: Performing deep debugging of complex LLM chains using Langfuse traces to identify bottlenecks and optimize for cost, latency, and context window usage.
• AI A/B Testing: Running systematic experiments across different models via OpenRouter (e.g., comparing Claude 3.5 Sonnet vs. GPT-4o) and analyzing results based on quantitative metrics.
• Data-Driven Decisions: Making deployment decisions for new prompts or models strictly based on quantitative benchmarks and trace data, rather than intuition.
• Output Scoring & Analysis: Developing scoring systems to analyze the “Problem → Solution” chain and identify root causes of hallucinations or logic errors using Langfuse analytics.
• Model Performance & Fine-Tuning: Regularly re-evaluating model performance as new architectures emerge and performing fine-tuning when necessary to meet specific domain requirements.

Qualifications

• Node.js & Next.js: Deep knowledge of the stack to build reliable services and handle complex LLM-generated data.
• Dynamic Prompting Skills: Proven experience in building prompts where content is highly dependent on input variables and context injection.
• OpenRouter Experience: Experience working with unified APIs, managing rate limits, and selecting the most cost-effective models for specific tasks.
• Langfuse (or similar): Understanding of LLM observability principles — setting up tracing, creating test datasets, and integrating scoring systems.
• Evaluation Methodology: Experience with frameworks like RAGAS or building custom “LLM-as-a-judge” systems.
• Analytical Mindset: Ability to transform raw generation logs into actionable business metrics and technical insights.
• Iterative Mindset: Focus on continuous product improvement through constant feedback loops.

Nice to have

• Fine-Tuning: Practical experience in fine-tuning models for specific domain tasks or JSON compliance.
• RAG Architecture: Understanding how to build and optimize Retrieval-Augmented Generation systems, including indexing, retrieval, and re-ranking.
• Python: Basic knowledge for working with data science scripts or AI evaluation libraries.

Location

Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours.

Benefits

Discover the perks of being part of our vibrant team! We offer:

• Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance.
• Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days.
• Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge.
• Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them.
• Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt

Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth!

Interview Process

After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps:

• Recruiter Screening (40 minutes)
• Technical Interview (60 minutes)
• Final Interview (30 minutes)

Life at Ruby Labs

At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day.

This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen.

Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success.

Backend AI Engineer

[Freelance, Full-time, Remote]

SNEAK PEEK

⇨ Location: Remote, GMT+0/+4

⇨ Interview process: HR Interview ⇨ Technical interview ⇨ Take-home challenge ⇨ Presentation of home challenge 

WHO ARE WE? 

At Rounds, we believe in harnessing the power of cutting-edge technology to drive business success. Our transformative, machine-learning technology identifies and optimizes mobile assets, while our team of experts, with their unparalleled human capital and business acumen, provides the strategic direction and support to turn mobile assets into profitable businesses. Together, we are revolutionizing the mobile industry. 

THE ROLE

We’re looking for a strong systems-oriented engineer with hands-on LLM experience to join our AI Innovation team. In this role, you’ll build AI systems and internal products that improve how teams work across different departments and areas in the company. The common denominator is ownership: you should be comfortable leading projects end-to-end, including clarifying needs with stakeholders, making decisions under ambiguity, and pushing through blockers when they arise.

This role is a strong fit for someone who enjoys both sides of applied AI work: full-stack engineering and practical use of LLM capabilities.

Hiring manager: Ori Nahum, AI Innovation Team Lead 

What you’ll be working on

Examples of projects you may work on:

• AI agents for code generation workflows (especially in mobile applications)
• A mobile app navigation agent
• Backend services that orchestrate LLM workflows, tool calling, and integrations with internal systems
• AI chatbot connected to internal data sources and business systems
• And other new AI-driven solutions that support different departments across the company

You’ll be expected to move between experimentation and implementation: validating ideas quickly, turning the promising ones into reliable tools, and leading projects far enough to make them useful in practice, not just technically possible.

WHAT ARE WE LOOKING FOR?

Must-have

• 5+ years experience in software development (preferably in Python, TypeScript, or mobile development).
• Ability to lead projects from idea to production, including aligning with stakeholders, driving decisions, and proactively removing blockers when needed
• Hands-on experience building LLM-based products, tools, or agents beyond toy prototypes
• Good understanding of prompt design, tool calling, orchestration, and how to make LLM systems actually useful
• Strong English communication skills

Big advantage

• Experience building internal developer tools or productivity systems
• Background in mobile development, especially native Android or iOS
• Design and implement evaluation frameworks to assess AI performance, accuracy, and reliability.
• Solid understanding of ML theory and how LLMs work under the hood, including key concepts, limitations, and trade-offs beyond the API layer
• Familiarity with cloud infrastructure / DevOps / CI-CD
• Good judgment around where AI adds value and where it doesn’t

Who will do well here

You’ll likely do well in this role if you:

• Like building practical systems, not just demos
• Take initiative without waiting for perfect specs
• Enjoy exploring new tools, but know how to separate hype from what’s actually useful
• Want the freedom to research, experiment, and then ship
• Enjoy working across different problem spaces and use cases, rather than staying in one narrow lane

INTERESTED?

Our recruitment process consists of the following steps: 

• HR interview with the recruitment manager: 45 min
• Technical interview with the AI Engineer Tech Lead & Team Lead: 1 hour
• Take-home challenge: ~ 4 hours of work
• Final Interview - take-home challenge presentation with CTO and AI Engineer Team Lead and Tech Lead: 1 hour

We're partnered with an AI company that cleans up and enriches messy product data (PDFs, spreadsheets, images, CAD files) turning it into clean, marketplace-ready catalogs for brands and retailers selling on Shopify, Amazon, Walmart, and large PIM/ERP systems. We're helping the company bring on a few more engineers – one of the positions is this Data Scientist one.

Stack: Python / FastAPI on the backend, React / Next.js on the frontend, LLMs throughout. 

Engagement: Full-time, fully remote.

=====

You'll own the ML that powers the enrichment, classification, and validation pipelines — the core of the product. Real data, large scale, noisy inputs, a lot of LLM work alongside classical ML.

What you'll do

• Build classification, extraction, and enrichment models over product data (text, images, metadata)
• Design and ship LLM pipelines – RAG, extraction, validation – in production, not just notebooks
• Run experiments and build evaluation frameworks you actually trust
• Work with engineering to deploy models, not hand them off

We're looking for

• 4-7+ years in data science / ML
• Strong Python (pandas, sklearn, PyTorch, TensorFlow, etc)
• Real experience with LLMs, NLP, CV
• Solid instincts on model evaluation and data quality
• You've worked on messy real-world data and know how to handle it
• You're comfortable working with a significant overlap with the US Pacific Time
• Your conversational English is strong (you will be speaking with your teammates daily)

Nice to have

• Product / catalog / e-commerce data experience
• Experience with vector DBs, embeddings, RAG in production

On behalf of our client, we are looking for a Senior Forward Deployed Engineer / Industrial AI Deployment Engineer (Python, Linux, PLC, Edge AI).

Responsibilities:

- Own the end-to-end lifecycle of AI deployment for manufacturing clients

- Work directly with customer operations and IT teams as the main technical contact

- Integrate AI vision systems with OT/IT/cloud stacks (OPC-UA, Modbus, PLCs, NVIDIA Jetson, ERP, cloud platforms)

- Build and iterate data pipelines (edge-to-cloud capture, deployment, monitoring, feedback loops)

- Troubleshoot software, networking, and integration issues in production environments

- Document architectures and configurations for handover and support

- Participate in pre-sales calls and contribute to product and engineering improvements

- Support on-site data collection and annotation

Requirements:

- 6+ years of technical experience

- 3+ years of experience with Python, Linux, Docker

- 3+ years of experience with production deployments or system integration

- 2+ years of experience in industrial automation or factory systems

- 2+ years of client-facing experience

- 1+ years of experience with PLC / OPC-UA / Modbus or industrial networking

- 1+ years of experience with computer vision or Edge AI

- Experience with cloud platforms (AWS, Azure, or GCP)

- Networking fundamentals (TCP/IP, VLANs, firewalls)

- Experience working with Git

- Professional English

Nice to Have:

- Experience in industrial automation or manufacturing environments involving OT/IT integration

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

appflame — Ukrainian product-driven tech company building world-class products: Hily, Taimi, AdConnect, Mailkeeper, and more.

About us:

• 7 years in the market, 500+ team members, offices in Kyiv, London, Limassol, and a co-working hub in Warsaw.
• In 2025, appflame ranked 5th among the top 50 employers in Ukraine according to Forbes and won the “Best Place for Growth” award.
• Our apps Hily and Taimi are among the top 5 dating apps in the US with over 70 million users. AdConnect and Mailkeeper focus on building proprietary B2B and B2C solutions.

Our mission:

• To put Ukrainian-built products on the global map.

Our goals:

• Break into the global top 5 product companies.
• Become a unicorn.
• Make Ukraine a country where unicorns are born.

We’re looking for bold, driven people who are passionate about building real products and dream of launching and scaling great startups. You bring the ambition — we provide the environment to make it happen.
 

What you’ll do:

• Design and develop an AI-powered productivity analytics platform — from data pipeline architecture to the final analytical product that helps teams make data-driven decisions.
• Build scalable LLM pipelines (Claude, GPT): develop data chunking strategies, implement MapReduce approaches for parallel processing of large datasets, and synthesize results into structured reports and insights.
• Create a meta-workflow system where LLMs generate, test, and deploy automation scripts in an isolated environment — with automatic self-correction loops and production deployment without manual intervention.
• Develop system-level prompt engineering: build and maintain a library of prompt templates for various analytical scenarios — from summaries and profiles to deep performance analysis.
• Build an evaluation framework for AI output quality control: hallucination detection, consistency scoring, regression tests — ensuring the product delivers reliable and reproducible results.
• Scale the platform to new domains and analysis types without linear growth in manual effort — through an architecture that allows adding new modules via configuration, not code.
• Document AI architecture, define automation specs, and present product insights to stakeholders and clients.
   

It’s a match if you have:

• 2+ years of experience working with LLMs in production: prompt engineering, pipeline development, API integration — with at least 1 year of hands-on experience with advanced features (tool use, structured outputs, agents).
• Strong Python skills (async, dataclasses, type hints, API integrations) and a commitment to writing clean, testable, and maintainable code.
• Understanding of MapReduce patterns for LLM processing: ability to choose chunking strategies, organize parallel processing, and aggregate results into a cohesive analytical product.
• Experience building agentic systems: tool use, self-correcting loops, multi-agent workflows — and the judgment to know when an agent works better than a rigid pipeline.
• Proficiency in SQL and experience working with analytical databases.
• English at C1 level — comfortable reading documentation, writing technical specs, and communicating asynchronously.
• Ownership mentality: you take tasks end-to-end, debug production issues independently, and iterate to deliver results without micromanagement.
   

Nice to have:

• Experience with orchestration/automation platforms (Windmill, Dagster, Prefect) — understanding how to build reliable automated workflows.
• Knowledge of RAG architectures, vector databases, and embedding pipelines — ability to build systems that work with large volumes of unstructured data.
• Experience building evaluation systems for LLMs (LangSmith, PromptFoo, or custom solutions) — understanding how to measure and improve AI product quality.
• Familiarity with Databricks / Delta Lake or Snowflake — experience working with modern data platforms.
• Experience working at product-driven tech companies or AI startups where you needed to build and iterate quickly.
• Understanding of product team metrics (DAU, retention, unit economics) and the ability to connect technical decisions to product impact.
   

Preferred tech stack:

Core:

• Languages: Python (primary), SQL
• LLM APIs: Claude API (Anthropic), OpenAI API
• Databases: PostgreSQL, ClickHouse
• Infrastructure: Docker, Git, FastAPI, Pydantic, pytest, asyncio

Nice to have:

• Languages: TypeScript/JavaScript, Bash
• LLM APIs: Google Gemini API
• Orchestration & Automation: Windmill, Dagster, Prefect, Airflow, Temporal
• RAG & Embeddings: LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, pgvector,FAISS
• Eval & Observability: LangSmith, PromptFoo, Weights & Biases, Arize AI
• Databases: Redis, MongoDB
• Data Platforms: Databricks, Delta Lake, Snowflake, BigQuery
• Infrastructure: Kubernetes, AWS (Lambda, SQS, S3), GCP
• CI/CD & DevOps: GitLab CI, GitHub Actions, Terraform

Hiring process: recruiter outreach > interview > test task > final interview > job offer.

About Bitmedia Labs
Bitmedia Labs - an international product IT company, has been in the industry since 2014, effectively functioning on a worldwide scale with a crew of 130+ ambitious and highly skilled professionals, creating successful projects in domains such as online advertising systems for the crypto space, blockchain games, and NFT products.

We are currently looking for an experienced engineer to join our R&D project, contributing to cutting-edge development and innovation within the company.

Required Qualifications:
 

• 3+ years of software engineering experience, with 2+ years working with LLMs and generative AI
• Strong Python development skills in a production environment (clean code, typing, testing, Git)
• Experience with both proprietary (OpenAI, Anthropic, Gemini) and open-source LLMs (LLaMA, Mistral)
• Working knowledge of orchestration frameworks (LangChain, LlamaIndex)
• Hands-on experience building RAG pipelines and working with vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar)
• Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT) and understanding of when to fine-tune vs. use RAG or prompt engineering
• Practical prompt engineering skills: structured outputs, function/tool calling
• Experience building backend services and APIs (FastAPI or Flask)
• Solid SQL skills and experience with databases (PostgreSQL, MongoDB, Redis, or Elasticsearch)
• Ability to debug LLM-specific issues (hallucinations, retrieval quality, cost/latency), work independently, and communicate technical decisions clearly.
   

Preferred Qualifications:
 

• Experience with agentic workflows and multi-step orchestration (LangGraph, CrewAI)
• Cloud deployment experience (AWS, GCP, or Azure), Docker, CI/CD
• Open-source model serving and inference optimization (vLLM, TGI, quantization, caching)
• Advanced retrieval techniques: hybrid search, reranking, query rewriting
• Familiarity with LLM evaluation and observability tools (RAGAS, DeepEval, LangSmith, Arize Phoenix)
• Knowledge of AI safety practices: prompt-injection prevention, PII handling, guardrails.

Hiring process: 
 

• Intro call with a Recruiter - Technical Interview with the Hiring team - Collection of Recommendations - Offer.
   

We offer:

• Flexible work environment - you can work remotely anywhere;
• The 8-hour working day with a flexible schedule;
• Competitive salary based on your experience;
• Regular performance review and annual salary review;
• Paid sick leaves, vacation, and holidays;
• Professional development tools (reimbursement of educational courses or workshops, conferences around the world);
• Ambitious team with transparent communication and a friendly atmosphere, no micromanagement;
• Apple equipment;
• Memorable gifts for holidays.

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

Now we are looking for a Software Development Engineer (MLOps) to join us as part of our team.

About the role

As a Senior ML Operations Engineer, you will support teams building and deploying AI-driven solutions, helping them overcome common challenges in the ML development, deployment, and support lifecycle. This role offers autonomy in decision-making, encouraging a proactive approach to solving complex issues and finding optimal solutions for scalable systems.

About the project

PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more.

Team composition

1 Engineering Manager, 4 Senior ML Ops Engineers

Work Environment

The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert, You will

• Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation.
• Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment.
• Provide mentorship, technical guidance, and perform code reviews for team members.
• Design and deliver on projects end-to-end with little to no guidance.
• Provide support to teams building and deploying AI applications by addressing common pain points in the MLDLC.
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities.
• Support the vision and values of the company through role modeling and encouraging desired behaviors.
• Participate in various cross-functional company initiatives and projects as requested.
• Contribute to strategic planning in a way that ensures the team is building exceptional products that bring real business value.
• Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance.

We’re looking for you if you have

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or equivalent practical experience).
• 5+ years of hands-on software development experience with Python (Java experience with strong Python proficiency also considered).
• 4+ years of experience designing and building distributed software systems and architectures.
• 3+ years of hands-on experience deploying and operating Machine Learning services in production.
• Experience supporting ML lifecycle operations including post-deployment monitoring and maintenance.
• Experience in cloud-native stack, with a practical understanding of containerization technologies such as Kubernetes and Docker.
• Demonstrated experience with SQL and NoSQL database design and implementation.
• Ability to decompose complex problems into iterative, well-defined solutions.
• Strong problem-solving abilities with focus on building scalable, efficient, and maintainable systems.
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions.
• Ability to be a team player who can also work independently.
• Experience working across multiple development teams is a plus.

Desired Skills

• Experience with cloud platforms (AWS, Google Cloud Platform, or Azure).
• Proficiency in GitOps practices and CI/CD pipeline development and management.
• Observability and monitoring: Integration experience with observability tools (Prometheus, Grafana) and building instrumented, production-ready systems.
• LLM Infrastructure: Experience provisioning and managing Large Language Models through managed services (Azure OpenAI, Google Vertex AI, Amazon Bedrock).
• LLM Tooling: Hands-on experience with LLM gateways (LiteLLM) and agentic frameworks (LangGraph, LangSmith, or similar).
• Vector Systems: Practical experience with vector embedding models and vector databases (Pinecone, Weaviate, Milvus, pgvector).
• RAG Systems: Experience building Retrieval-Augmented Generation systems and evaluating both retrieval quality and generation performance.
• Cloud-native experience with services like Amazon SageMaker, Google Vertex AI, or Azure ML
• Familiarity with ML frameworks and tools: PyTorch, TensorFlow, scikit-learn
• Experience with data infrastructure: Redis, Elasticsearch, Apache Kafka.
• ML experiment tracking and model management: Weights & Biases, MLflow, KubeFlow.
• API development with FastAPI or similar frameworks.
• Java programming experience is a plus.

Interview Process

1. Pre-Screening with the recruiter
2. Tech Interview(ML Fundamentals, Software Engineering) + Live Coding (up to 1,5 hours)
3. ML System Design Interview (up to 60 min)
4. Interview with Engineering Manager (60 min)
5. Final Client Interview (60 min)

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.

We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.

Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Computer Vision Engineer to join a project with a global leader in biomedical imaging. The company offers a comprehensive product portfolio for Karyotyping, H&E, IHC, and FISH analysis, providing advanced imaging and analysis tools for Pathology, Cytogenetics, and Research laboratories. This role involves working on cutting-edge solutions that enable high-precision diagnostics and support innovation in scientific research.

Key Requirements:

🔹 5+ years of hands-on experience in algorithm development using Python (must) and C++ (advantage);
🔹 Proven experience in training, fine-tuning, and deploying AI/ML models – Must;
🔹 Experience in Computer Vision (e.g., Shape Analysis) / Image Processing using image processing libraries like OpenCV in C++ – Advantage;
🔹 Strong ability to work independently as well as in a SCRUM team under Agile dynamic environment; proactive and self-driven;
🔹 Methodical, solution-oriented mindset with a strong “can-do” approach;
🔹 MSc or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Physics, or a related field – Must;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Research and develop advanced algorithms in Machine Learning, Neural Networks, Computer Vision, Image & Signal Processing, to be integrated into ASI products;
🔹 Define software specifications and deliver production-ready code that meets project milestones, while addressing constraints such as computational resources, response time, and memory consumption (GPU and CPU);
🔹 Train, optimize, validate and Integrate AI/ML models for diagnostic and imaging applications using Python and its libraries (PyTorch, NumPy, etc);
🔹 Collaborate closely with cross-functional teams, including R&D, Applications, and Product groups;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.

Sii Ukraine is a subsidiary of Sii Poland — the leader in IT, engineering, and consultancy services with over 7500 IT experts in Poland and more than 250 prestigious customers. We are looking for ambitious and top-quality professionals to join our project teams. 

We are seeking an AI Leader with a holistic understanding of modern AI technologies - including classical machine learning, deep learning, and especially the latest advancements in generative AI. This role requires not only deep technical literacy but also the ability to guide teams, mentor talent, and foster a high-performing, collaborative AI organization. As a people-first leader, this individual will inspire and develop multidisciplinary teams, influence stakeholders, and ensure alignment between technical execution and business goals. The role may involve spending up to 70% of the time on non-technical activities such as stakeholder engagement, cross-functional leadership, and supporting business development or sales initiatives.

Responsibilities:

• Develop, mentor, and empower multidisciplinary AI teams, including data scientists, engineers, and product managers—by setting clear expectations, providing coaching, and cultivating a collaborative, high-performing culture.
• Drive talent strategy for the AI organization, including hiring, onboarding, performance management, and building a diverse and inclusive team with strong technical and interpersonal skills.
• Design and oversee end-to-end AI system architectures, ensuring seamless integration of machine learning models, data pipelines, and infrastructure while guiding teams toward scalable, high-quality solutions.
• Champion innovation by staying current with cutting-edge AI research, emerging technologies, and experimental techniques, and by encouraging continuous learning across the organization.
• Represent the AI function in customer-facing and executive-level engagements, delivering technical presentations, leading discussions, addressing complex inquiries, and clearly articulating AI value propositions and solution feasibility.

Requirements:

• 10+ years of experience delivering customer-facing AI solutions, including 5+ years in a leadership or equivalent strategic role guiding teams and driving end-to-end AI initiatives.
• Deep technical expertise across AI models, algorithms, and tooling, with strong proficiency in at least one major cloud provider’s AI/ML ecosystem (AWS, GCP, or Azure).
• Proven ability to work cross-functionally with product, engineering, sales, and executive stakeholders to translate complex, cloud-based AI capabilities into clear, high-impact business outcomes.
• Demonstrated commitment to continuous learning, maintaining up-to-date knowledge of emerging cloud AI services, machine learning infrastructure advancements, and evolving industry best practices.
• Exceptional communication, leadership, and people-management skills, with a track record of hiring, developing, and enabling high-performing AI teams.
• Excellent command of English, enabling effective and fluent communication
• Tax residence in Ukraine and fluency in Ukrainian is required

About Sprinterra
Sprinterra is a technology and consulting company delivering custom software solutions and digital transformation initiatives for clients in the US and Europe. We combine strong engineering practices, Agile delivery, and business-oriented thinking. A key focus for Sprinterra is the adoption of AI-driven solutions - both internally and in client projects - to significantly increase efficiency, quality, and scalability.

Role Overview
We are looking for a senior executive technology leader who will own and drive Sprinterra's overall Technology and AI vision at the company level. This role carries full responsibility for defining, implementing, and scaling our AI-first transformation strategy across internal operations, delivery models, and client solutions.

The primary objective is to reposition Sprinterra as an AI-enabled organization by systematically transitioning from traditional manual processes to AI Agents, intelligent automation, and augmented engineering workflows.

This role operates at the executive level in close partnership with the Management Board, contributing to company-wide strategic decisions, investment priorities, capability development, and long-term technology positioning.

The Technology & AI Strategy Lead combines strategic leadership with architectural oversight and hands-on technical credibility. In addition to setting direction, this leader ensures execution, guiding teams, shaping complex solution architectures, supporting pre-sales initiatives, mentoring senior engineers, and acting as the ultimate technical authority within the organization.

Why join Sprinterra?
This is a rare opportunity to define and implement an AI-first transformation from the ground up. You will shape how a growing international technology company evolves its delivery model, internal operations, and client solutions through AI Agents and intelligent automation.

As Technology & AI Strategy Lead, you will operate as a key executive partner to the Management Board, directly influencing company strategy, investment priorities, and long-term market positioning.

Your decisions will shape:

• How we work
• What we build
• How we compete
• How we scale

Key Responsibilities
AI & Technology Strategy

• Define, own, and continuously evolve Sprinterra's overall Technology and AI strategy at the company level
• Identify and prioritize strategic opportunities to transition from traditional delivery models to AI Agents, LLM-driven workflows, and intelligent automation
• Establish and govern a long-term AI transformation roadmap fully aligned with business objectives, growth targets, and market positioning
• Advise and report to the Management Board on technology vision, investment priorities, progress, risks, and measurable outcomes
• Lead company-wide adoption of AI tools, frameworks, and engineering standards
• Drive organizational evolution toward AI-augmented delivery models and next-generation engineering practices
• Define and enforce standards, governance models, and best practices for responsible, secure, and scalable AI implementation
• Ensure all AI initiatives meet enterprise-grade expectations in quality, security, compliance, and ethical responsibility

Hands-on Engineering & Architecture

• Provide executive-level technical oversight and intervene hands-on in strategically critical or high-complexity projects when required
• Define architectural principles and review system and AI architectures across the organization
• Ensure solutions are scalable, secure, maintainable, and aligned with long-term technology strategy
• Act as the ultimate technical authority and escalation point for complex architectural or engineering challenges

Pre-Sales & Technical Sales

• Lead and shape technical pre-sales strategy in collaboration with Sales and Delivery leadership
• Define high-level system architectures and AI-driven solution approaches for strategic client proposals
• Serve as a trusted executive-level technical advisor in client meetings, workshops, and negotiations
• Translate complex business challenges into differentiated, AI-enabled technology solutions that strengthen Sprinterra's market position

Required Skills & Experience

• 10+ years of progressive experience in software engineering, system architecture, and technology leadership
• Proven track record of defining and executing company-level technology and AI strategies
• Strong practical experience with AI/ML, LLMs, AI Agents, and intelligent automation in production environments
• Demonstrated ability to lead large-scale technology transformations, not just individual projects
• Hands-on technical background with the ability to dive deep when strategically necessary
• Experience aligning technology initiatives with business strategy, growth objectives, and market positioning
• Executive-level communication skills, with the ability to influence board members, senior stakeholders, and clients
• Experience leading technical pre-sales, shaping solution strategy, and representing technology at the executive client level
• Strategic leader with full ownership mindset and accountability for outcomes
• Capable of balancing long-term vision with disciplined execution
• Confident decision-maker comfortable operating with ambiguity and high impact
• Influential communicator able to align leadership, engineering, and business teams
• Drives change rather than maintaining status quo
• Trusted advisor to executive leadership and key clients

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide
 

About your role: We’re looking for an AI Engineer who wants to build production-grade AI systems, not just experiment with demos. This is a high-ownership, greenfield role where you’ll help build our AI platform from scratch, working directly with the Head of AI.  You’ll own initiatives end-to-end — from discovery and architecture decisions to production delivery — and play a key role in shaping how AI is used across the company.

You’ll work with a modern AI stack including Claude/OpenAI/Bedrock, RAG pipelines, eval frameworks (Promptfoo, Ragas, LangSmith), and agentic patterns. This role is ideal for someone who enjoys autonomy, strong engineering ownership, and proactively identifying the next highest-leverage opportunity to drive into production.

In this role, you will:

• Design and build RAG and automation workflows inside our VPC environment.
• Create integrations across engineering, communication, and knowledge-management systems (Jira, Confluence, Slack, Google Drive, Git).
• Develop AI-powered pipelines for code quality checks, ticket auto-classification, documentation updates, release notes, and meeting summaries.
• Work on prompt engineering, model selection and routing (Haiku / Sonnet / Opus), and workflow optimization.
• Build evaluation and regression frameworks for AI workflows to prevent model-upgrade regressions.
• Create lightweight dashboards for engineering leads to surface delivery patterns and bottlenecks.
• Own initiatives end-to-end: scope → design → ship → measure → iterate.

It’s all about you:

• 5+ years of production experience with Python (services, async, API integrations, clean and testable code).
• Hands-on experience with LLM APIs in production: Anthropic Claude (Opus/Sonnet/Haiku), OpenAI, AWS Bedrock.
• Strong understanding of RAG systems: chunking, embeddings, hybrid search, re-ranking, grounding/citations.
• Prompt engineering + structured outputs + tool/function calling.
• Experience with eval/regression frameworks: Promptfoo, Ragas, LangSmith, or custom evaluation harnesses.
• Agentic patterns: ReAct, function-calling loops, fallbacks.
• Vector databases: pgvector, Pinecone.
• Workflow orchestration: n8n, Airflow, or custom orchestration systems.
• Observability: token-spend tracing, latency monitoring, model routing.
• Solid AWS fundamentals: IAM, Lambda, S3, CloudTrail — comfortable deploying inside VPC environments independently.
• CI/CD + pipeline hooks (GitLab/GitHub), webhooks, event-driven architectures.
• Basic SQL skills for analytical queries and metrics dashboards.
• Driver mindset: proactively identifies the highest-leverage opportunity and drives it to production
• B2 English level

Would be a plus:

• Real REST integrations with 2–3+ APIs
• Experience with workflow orchestration tools.
• Prompt evaluation tooling such as  LangSmith is nice to have
• Experience with Docker
• RAG experience: embeddings and vector stores (pgvector, Pinecone, or similar) for knowledge base use cases

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process:

• Intro call
• Technical Interview
• Final Interview
• Reference check
• Offer