Jobs ML / AI

Location: EU
Workload: Full-time
Duration: Long-term

About the role

We are looking for a Senior AI Solution Architect with strong experience in the Microsoft ecosystem and solid expertise in designing enterprise-grade AI solutions. In this role, you will lead architecture decisions for modern AI-driven applications, including solutions based on RAG patterns, Azure AI services, and generative AI technologies.

You will work in a consulting-style environment, helping shape scalable, secure, and production-ready architectures for clients across the EU.

Key responsibilities

• Design end-to-end architecture for AI and cloud-native solutions on Azure
• Lead implementation of solutions leveraging RAG, Azure OpenAI, and related AI services
• Define scalable application architecture using Azure PaaS services
• Integrate AI capabilities such as search, OCR, vision, and content enrichment into business solutions
• Collaborate with engineering and DevOps teams to ensure reliable delivery pipelines
• Support architectural governance, technical decision-making, and best practices
• Translate business requirements into robust technical designs

Required skills and experience

• 8+ years of overall experience with the Microsoft application stack
• Proven background as an Azure Architect in a consulting environment
• Hands-on experience with AI solution implementation
• Strong understanding of prompt engineering techniques
• Experience implementing Retrieval-Augmented Generation (RAG) solutions
• Strong knowledge of:
  • Architecture design
  • Azure PaaS: Container Apps, Functions, Web Apps, Storage
  • Azure Cognitive Services: Azure AI Search, OCR, Vision, etc.
  • Azure AI Foundry or Azure OpenAI
  • Microsoft Fabric, Azure Data Factory, or Databricks
  • Azure DevOps Pipelines or equivalent CI/CD tooling
  • .NET 6+ or Python
• Native-level English

Nice to have

• Experience with Azure OpenAI or other generative AI technologies such as GPT
• Microsoft certifications such as:
  • AZ-900
  • AZ-204
  • AZ-300
  • AZ-400
  • DP-900
  • AI-102

What we offer

• Long-term full-time engagement
• Opportunity to work on modern enterprise AI initiatives
• International environment with EU-based delivery
• High-impact architectural role in a growing AI space

Remote · Contract · EU time zone preferred · Capacity: propose what the scope needs.

We pay for outcomes, not hours. You own the pipeline; we own the product.

Contract engagement, scope-driven. Propose your own structure — trial period, fixed-price milestones, retainer, or a hybrid. Whatever fits how you actually work.
 

We're building the definitive structured quality, safety & value dataset for the global supplement market. Two customers: consumers (React Native app) and AI systems (structured API). The data pipeline IS the product. 
 

What you deliver:

A pipeline that generalizes across our module types: boolean classification, multi-class classification, characteristic extraction, entity extraction, entity linking/grouping, and structured attribute profiling.
Core deliverables:

• Golden-record schema and workflow that works for any of the above, co-built with our regulatory SME
• Eval harness in CI — accuracy reported on every commit, per module
• Versioned prompt/rule system with rollback
• Measured, reproducible accuracy numbers on held-out sets, per module, against written gates
• A workflow our SME can operate without a developer in the loop

Success = numbers we trust, on sets we trust, with a pipeline that won't silently regress — and a framework that scales to every remaining module without rework.
 

Stack: Python, DSPy, vLLM, PaddleOCR, RT-DETR, open-weight VLMs and LLMs. Laravel/Filament backend (you consume it, our backend team maintains it).
 

Required:

• 3+ years shipping production ML/data pipelines — not research
• Prompt optimization at scale: DSPy / BootstrapFewShot / MIPROv2, or equivalent (LangChain + pytest eval harness counts)
• VLM inference serving (vLLM / TGI / llama.cpp)
• OCR pipelines wired to detection models
• Eval-first: you ship the harness before the pipeline
• Clean Python, git discipline, versioned prompts
• You've maintained a pipeline in production for 12+ months (not just built and handed off

Not a fit if you:

• Propose RAG for structured extraction
• Want to fine-tune before prompt-optimizing
• Want to pre-train a domain model
• Need a PM to translate goals into tickets
   

Nice to have: Comfortable reading enough PHP/Laravel to integrate with our Filament admin.

We provide: 

• Direct CEO collaboration — fast decisions.
• Regulatory SME owns golden records and sign-off
• Backend team handles schema and infra
• Written acceptance criteria before each module
   

Compensation: fixed-price per milestone, or retainer. Propose your structure with application.
 

How to apply?

Fill out questioner below and submit.

NB. No cover letters. No AI-generated applications — we'll notice.

You will be a player in the AI-Data Delivery Pod, contributing to enterprise solutions that turn complex domain documentation into machine-usable intelligence. The focus is on building “Self-Evolving Knowledge Bases” that power intelligent assistants and decision-support systems. You will operate within a high-speed delivery environment where the synergy between human expertise and agentic execution is the primary driver of success, all integrated within the client’s existing Azure infrastructure.

We are looking for a Trainee AI / ML Engineer (Generative AI) to join our AI & Data practice. This role is designed for an early-career, AI-native engineer who is comfortable using modern GenAI tools and wants to grow on real projects under the guidance of senior ML / AI experts.

You will help rapidly prototype ideas, build small PoCs, and experiment with solutions based on large language models (LLMs) and other generative AI techniques. Your focus will be to implement well-defined tasks, run experiments, and use GenAI tools to speed up coding, analysis, and documentation – while learning how to do this safely and reliably in production-oriented environments.

Requirements

• Some experience in software development, data science, or ML (commercial experience, internships, or strong personal projects).
• Solid basic skills in Python and core data/ML libraries (e.g., NumPy, pandas, Scikit-learn).
• Understanding of fundamental ML concepts (datasets, train/validation split, basic metrics, overfitting).
• Practical familiarity with generative AI / LLMs:
   – regular use of tools like ChatGPT, Copilot or similar for coding and data tasks;
   – basic understanding of prompts, context windows, and common limitations (hallucinations, privacy, bias).
• High motivation to learn, ask questions, and accept feedback.
• Organized and responsible: able to follow a spec, document work, and meet agreed timelines.

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
• Course work, pet projects, or a thesis related to ML, NLP, or Generative AI.
• Basic exposure to RAG, embeddings, or vector databases (from articles, courses, or small experiments).
• Familiarity with at least one cloud platform (Azure, AWS, or GCP) from labs or online courses.
• Experience with Jupyter notebooks, Git, and simple CI/CD or MLOps tools (even at a “student project” level).
• Participation in hackathons, Kaggle competitions, or open-source projects.

Responsibilities: 

• Rapidly prototype and iterate on ML / GenAI ideas in notebooks and scripts, turning high-level concepts into small PoCs and demo flows.
• Implement well-defined tasks in Python (data preprocessing, basic model training, evaluation scripts, and utility functions) as part of prototypes and production-oriented components.
• Assist in experiments with LLMs and GenAI APIs (prompt variants, small workflows, simple RAG setups) under the guidance of senior engineers, proactively suggesting new options and documenting what works and what doesn’t.
• Use GenAI tools to support your daily work (coding, tests, documentation, exploratory analysis) and capture key findings in a clear, structured way.
• Prepare and clean datasets, run experiments, and summarize results in concise formats (tables, short reports, simple dashboards).
• Help build and maintain demo environments and internal PoCs for ML / GenAI use cases, keeping them reproducible and easy to reuse.
• Follow coding standards, version control practices, and basic quality processes (code reviews, simple tests, logging).
• Actively learn from senior team members, ask questions, and gradually take ownership of small components within larger solutions.

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

We are looking for a Founding Engineer to join a fast-growing start-up developing a product for automated lead generation and recruitment outreach.  

Responsibilities: 

- Autonomously architect, prototype, & build the product from the ground up.

- Develop integrations with AI (e.g. Perplexity, OpenAI) & 3rd party API (e.g. CRMs).

- Leverage your prompt engineering skills to maximize the outcome.

- Horizontally work with founders in discussions on business & product topics.

Requirements: 

- 1+ years of experience in a SaaS/startup previously. 

- Senior-level engineer with 5+ years of software development experience. 
- Experience in RAG & AI agents development and prompt engineering.
- API development and integration experience.
- Database design and optimization (SQL).
- Development in cloud infrastructure (AWS/GCP/Azure).
- Patterns for asynchronous task processing (RabbitMQ, SQS, or similar).
- Experience with n8n/make will be a great plus.

- Authentic obsession with giving customers the best.
- Excellent verbal communication skills.

- Excellent English, strong B2 level minimum.

Job details:

• Full-time.
• Fully remote.
• Long-term.
• B2B contract.
• Start date — ideally ASAP / by mid-April.
• Also, you will get founding member equity % in addition to your fixed salary.

What else will you get:

- Learning how a startup grows.

- Direct impact on product and company strategy.

- Deliver value directly to paying B2B clients.

- Opportunity to build and lead a team and department.

- You will work with the most modern toolset (including Cursor in Agent mode).

The hiring process: 

• 45 min pre-screen interview with a recruitment manager
• 15-30 min call with the client
• a technical deep-dive interview, most likely with online coding (conducted by client)
• online call with the team or key team members

Project Overview
The project focuses on building a production-ready enterprise AI chatbot on SAP BTP Kyma, leveraging modern AI and backend technologies such as SAP Joule, Node.js/TypeScript, NestJS, mastra AI, OpenSearch, and SAP HANA.

The platform emphasizes AI architecture, reliability, and scalability, enabling advanced RAG pipelines, agent-based capabilities, and secure enterprise integrations. Strong engineering practices, observability, and AI quality evaluation are key success factors.


Role Responsibilities
As an AI Developer, the consultant will:

• Design and implement agentic AI capabilities, including tool/function calling, planning, memory/state handling, safety guardrails, and failure recovery
• Build and optimize advanced RAG pipelines on OpenSearch (hybrid retrieval, embeddings, rerankers, query rewriting, retrieval evaluation)
• Develop and maintain API and MCP integrations, including MCP servers/clients, capability manifests, and clean, versioned REST/WebSocket APIs
• Create and iterate prompt strategies, including tool-aware prompting, structured outputs (JSON), and prompt governance
• Establish AI quality evaluation and testing, using tools such as RAGAS and/or DeepEval, including regression testing and red-teaming
• Implement secure and performant data access with SAP HANA using TypeORM
• Ensure observability and performance monitoring using Dynatrace (latency, cost, quality, SLIs/SLOs)
• Build and maintain CI/CD pipelines for Kyma/Kubernetes environments

Collaborate closely with product and architecture teams, document designs, and participate in technical reviews

Mandatory Skills and Experience — MUST HAVE !!!

• Proven production AI adoption, including agentic or advanced RAG solutions with measurable impact
• Strong experience with advanced RAG on OpenSearch (vector and hybrid search, indexing strategies, retrieval evaluation)
• Experience with agent frameworks and patterns (multi-step planning, tool integration, memory/state, guardrails)
• Hands-on experience with AI evaluation and testing (RAGAS, DeepEval, or similar)
• Strong Node.js and TypeScript skills; solid API engineering (REST/WebSockets, OpenAPI, versioning)
• NestJS experience in enterprise-grade services
• Experience with MCP integrations in production or strong evidence of rapid ramp-up capability
• Strong experience with SAP HANA and TypeORM
• CI/CD experience for containerized applications on Kyma/Kubernetes
• Dynatrace experience for observability and performance monitoring
• Security-first mindset (OAuth2/OIDC, JWT, RBAC, secure secrets handling)
• Ability to learn quickly and work within complex enterprise architectures
• Fluent English
  
  
  Nice to Have
• SAP ecosystem knowledge; SAP Joule experience is a plus
• Experience with mastra AI or similar AI orchestration frameworks
• Advanced prompt engineering skills and prompt governance workflows
• Experience integrating AI into web frontends (streaming responses, SSE, rate/cost controls)
• Experience with multiple LLM providers and routing strategies
• Knowledge of data privacy and compliance (e.g. GDPR-aware AI design)

Project Details
Start: ASAP
Duration: Until 31.10.2026 (extensions possible)
Estimated Effort: 960 hours
Location: Fully remote
Language: English
Candidate Location: EU

We are looking for a Senior Copilot Studio AI Developer to design, build, and optimize AI agents using Microsoft Copilot Studio for enterprise clients.

You will work on intelligent automation solutions where AI agents support internal operations, customer service, document handling, workflow execution, and business productivity improvements.

Responsibilities

• Design and develop AI agents in Copilot Studio
• Configure prompts, conversation flows, logic, actions, and agent behaviors
• Integrate agents with enterprise data sources, APIs, Microsoft ecosystem tools, and workflows
• Build automations using Power Platform components
• Test, monitor, and optimize agent performance and response quality
• Improve usability, reliability, and business efficiency of AI solutions
• Work with stakeholders to translate business needs into AI assistants

Requirements

• 4+ years of commercial experience in software / automation / AI solutions
• Hands-on experience with Microsoft Copilot Studio
• Strong knowledge of Power Platform (Power Automate, Power Apps is a plus)
• Experience with conversational AI / LLM-based systems
• Understanding of prompts, orchestration logic, integrations, and workflows
• Good spoken and written English
• Strong communication skills in client-facing environments

Nice to Have

• Experience with Azure ecosystem
• Knowledge of enterprise automation processes
• Experience integrating CRM / ERP / document systems
• Prompt engineering experience

Conditions

• Duration: 6+ months
• Remote

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.

We are looking for a Senior ML & AI Engineer to join us as part of our team.

About the role

PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical, and everyone has the opportunity to shape the long-term direction of our team.

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

Engineering Manager, 6 ML & AI 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

• Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges.
• Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis.
• Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights.
• Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing.
• Mentor & Lead: Act as a mentor for junior team members and stay updated on trends in Agentic AI, transformer models, and generative systems.
• Collaborate & Communicate: Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively.
• Tech Stack & Focus Areas:
• Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems.
• Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources.

We’re looking for you if you have:

• Educational Background: You hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field.
• Experience: You bring 4+ years of production experience in the ML field, with a track record in developing transformer-based models and deploying them in scalable systems.

• Technical Expertise:

  - Proficient in Python and machine and deep learning frameworks like TensorFlow, PyTorch, ScikitLearn, Spacy, or others.

  - Experienced in natural language processing and modern LLM-based techniques.

  - Experience with full ML lifecycle, data preprocessing, training, evaluation stage, and monitoring techniques.

  - Skilled with SQL and data extraction methods.

• Innovative Thinker: You thrive on solving complex problems and are always exploring new trends in Generative AI.
• Collaborator & Communicator: You’re an excellent communicator able to collaborate and professionally express your thoughts to team members, other engineering teams, and stakeholders.
• Domain Knowledge: Exposure to financial services, investment banking, venture capital, or private equity is nice to have.

What’s in it for You

Reveal great tech solutions

Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.

Experience an agile and flexible working environment

Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.

Embrace the opportunity for personal and professional growth

Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learning through the corporate library, public speaking support, and more.

Be among like-minded people

Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.

Interview steps

• Pre-Screening with the recruiter
• Technical interview (up to 90 min)
• System Design interview (up to 45 min)
• Behavioral Round with Product Manager (45 min)
• Final interview with Engineering Manager (60 min).

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).

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/1tzxGX4Uu7Ts_HCLFXESKLnKaaBfVCPf1f9AYZPrkjJM/preview?tab=t.0

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)

Are you passionate about safeguarding countries, societies, and businesses from information threats? Look no further! Our rapidly scaling company is passionately committed to this crucial mission, offering you a privileged opportunity to collaborate with some of the world’s most influential organizations, including NATO and the EU.

If you’re ready to join a dynamic team working towards a common vision of a safer digital world, we invite you to be a part of our journey. Shape the future with us and help defend against online threats with purpose and innovation!
 

Role Overview

We’re looking for a Senior AI Engineer with a solid engineering background and hands-on AI experience. In this role, you will help design and implement innovative AI-powered solutions that are core to our platform’s mission. You’ll work across the stack to build and integrate AI capabilities that are both scalable and practical.

You won’t need to build everything from scratch, but you’ll need the skills to fine-tune, adapt, and creatively apply state-of-the-art models and tools to solve real-world problems. Your responsibilities will range from working on backend services to shaping AI agents and LLM-based pipelines for production use.
 

Key Responsibilities

• Understand business challenges and generate innovative ideas to address them using AI and machine learning.
• Research, evaluate, and adapt existing deep learning and machine learning models for practical applications.
• Develop cost-efficient, scalable AI solutions.
• Develop and maintain services for data enrichment using LLMs.
• Design and build AI agentic systems for dynamic use cases.
• Monitor industry advancements and identify opportunities to leverage the latest tools and techniques.

Requirements

Engineering Skills:

• Strong Python skills.
• Experience with FastAPI, Docker, and asynchronous programming.
• Good knowledge of DBs, including PostgreSQL, Elasticsearch, and Vector DBs.

AI Skills:

• At least 3+ years of hands-on experience in AI/ML, with a focus on LLM-based systems.
• Proven experience building RAG systems in production.
• Experience designing and implementing agentic systems.
• Strong understanding of transformer architectures.
• Practical experience with prompt engineering.
• Knowledge of LLM infrastructure and deployment.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Understanding of evaluation methodologies for LLM outputs

We Offer

• Opportunity to contribute to a mission-driven startup and support prestigious clients, including governments worldwide, enterprise clients, and leading NGOs in addressing information threats and tackling security challenges.
• Autonomy and freedom to drive experiments and bring your own ideas to life.
• Flexibility of fully remote work.
• Flexible, unlimited time-off policy.

Responsibilities:

• Own and support core ML infrastructure (MLflow, CVAT, GPU/CPU cloud instances, internal data tools).
• Assist Data Engineers with deploying and maintaining data pipelines.
• Act as the primary contact for ML and Data teams on infra-related requests.
• Improve reliability and efficiency by adding automation, monitoring, and tooling enhancements.
   

Must have:

• Knowledge of Python, Terraform, Docker, Linux.
• Hands-on experience with cloud environments (Azure prefered).
• Understanding of the end-to-end ML lifecycle (data → training → evaluation → deployment → monitoring).

Nice to have:

• Familiarity with Kubernetes.
• Experience with FFmpeg or GStreamer for video processing and streaming.
• Experience with model serving frameworks and inference formats (ONNX, TensorRT, OpenVINO, NVIDIA Triton).
• Experience deploying computer vision models, especially to edge/embedded devices (NVIDIA Jetson, Intel platforms, Raspberry Pi).

• Надаємо бронювання від мобілізації

Start date: ASAP

What you’ll do

• Provide technical leadership for AI projects, guiding teams through the treatment of structured and unstructured data for AI processing.
• Oversee backend development (primarily .NET) and ensure solutions meet performance and scalability requirements on Azure.
• Collaborate with product owners and stakeholders to define scope, deliverables and timelines for AI initiatives.
• Mentor team members, fostering a proactive and autonomous culture and ensuring clear communication across disciplines.
• Drive continuous improvement and adopt best practices in AI development; optionally support front‑end integration (React) and SharePoint Online interoperability.

Requirements

• Proven experience leading AI/ML projects from inception to deployment, including data preparation and model operationalisation.
• Strong backend development skills with .NET and familiarity with Azure services.
• Excellent communication, leadership and organisational skills; ability to work autonomously.
• Nice to have: experience with front‑end development (React) and SharePoint Online integration.

We offer

• Leadership role with significant influence over AI strategy and roadmap.
• Opportunity to shape a growing team and work with state‑of‑the‑art AI technologies.
• Remote‑friendly environment with flexible schedule and competitive compensation.

Start date: ASAP

What you’ll do

• Design, develop and maintain cloud‑native full‑stack applications with an emphasis on performance, scalability and security.
• Build responsive front‑end interfaces using React, Angular or Vue; integrate back‑end services via RESTful APIs and serverless architectures.
• Collaborate with architects and business analysts to translate business requirements into robust technical solutions.
• Research and prototype new technologies, including Generative AI models, and integrate AI‑driven features such as chatbots, predictive analytics and intelligent content generation.
• Produce technical documentation, support presales/marketing efforts and seek opportunities for optimization and automation while adhering to best practices.

Requirements

• 4+ years’ experience with .NET 6+ and cloud platforms (preferably Microsoft Azure); solid understanding of RESTful API design and OpenAPI.
• Proficiency with both SQL and NoSQL databases; experience with integration and event‑driven architectures.
• Familiarity with front‑end frameworks (React, Angular or Vue) and Agile methodologies (Scrum).
• Nice to have: practical experience with Generative AI models (GPT, DALL‑E) and AI frameworks (PromptFlow, TensorFlow, PyTorch, Azure Cognitive Services); ability to integrate AI functionality (chatbots, personalised content) into web apps.
• Comfortable working independently, proactively and communicating with stakeholders.

We offer

• A chance to work on innovative AI‑powered cloud applications.
• Flexible work arrangements with supportive team and opportunities to experiment with cutting‑edge AI technologies.
• Competitive salary, paid vacation and professional development budget.

EXITEK team is looking for a Machine Learning Engineer. We're expanding our development team and looking for a passionate, experienced, self-organised candidate to work on our BeautyUp app (https://apps.apple.com/us/app/id1671843069).

Responsibilities:

• Design, develop, and optimize state-of-the-art computer vision pipelines, algorithms and models;
• Conceive and experiment with innovative features and functionalities in the realm of photo editing and enhancement;
• Collaborate with cross-functional teams to integrate machine learning models into production systems and pipelines.

Requirements:

• Proficiency in Python and PyTorch;
• Experience in Computer Vision (GANs, SD, etc.) is a must;
• Deep understanding of the current state of the art in machine learning and computer vision;
• Robust communication skills, complemented by the ability to thrive in a collaborative team environment.

We’re building an intelligent AI agent that doesn’t just answer questions, but reasons, retrieves, understands context, and acts across documents, SQL data, and visual inputs.

If you're excited by rapid experimentation, real users, and pushing LLMs beyond chat - this role is for you.

     What You'll Do

• Design and implement an intelligent chatbot/agent capable of reasoning over documents, structured SQL data, and multimodal inputs
• Fine-tune or integrate LLMs (OpenAI, Ollama, Deepseek, etc.) for contextual Q&A
• Develop text analytics pipelines (sentiment analysis, classification, topic modeling)
• Design image processing systems for tagging, feature extraction
• Experiment rapidly with new ideas, validate hypotheses
• Support and work with Hadoop clusters for big data processing.
  
  What We're Looking For
• 2+ years of experience as ML/AI engineering or in a similar role
• Bachelor’s degree in Computer Science, or a related field
• Strong proficiency in Python, and solid experience with ML frameworks
• Deep understanding of NLP and CV fundamentals
• Hands-on experience with AI/ML projects deployed in production
• Experience integrating LLMs, retrieval pipelines in multi-step reasoning agents
• Practical experience in text/image processing
  
  Nice to Have
• Knowledge of OCR, captioning
• Experience with prompt engineering
• Experience in predictive modeling