Jobs ML / AI

About the team:

The AI Platform team is a newly formed, high-impact group responsible for driving AI adoption across the entire organization. Reporting to a Team Lead, you will join a team of 4 engineers building cutting-edge AI solutions from the ground up. This is a unique opportunity to shape the AI strategy and tooling that will transform how the company operates.

The role:

As a Senior Software Engineer on the AI Platform team, you will design, build, and deploy production-grade AI systems that enhance productivity and decision-making across all business units. You will be a technical expert and advocate for agentic AI solutions, enabling engineering teams company-wide to leverage AI effectively.

Key Responsibilities:

•       Design and build Retrieval-Augmented Generation (RAG) systems to provide intelligent, context-aware solutions for internal and external use cases

•       Develop AI agents that automate workflows and enhance business processes across the organization

•       Serve as an internal expert on agentic AI, guiding and mentoring engineering teams on best practices for building and integrating AI agents

•       Evaluate, integrate, and deploy the latest AI technologies, frameworks, and models to keep the company at the forefront of innovation

•       Collaborate cross-functionally with product, engineering, and business stakeholders to identify high-impact AI opportunities

•       Contribute to architectural decisions and help shape the technical direction of the AI Platform

Required Qualification:

•       5+ years of software engineering experience with strong proficiency in Python, TypeScript, or Java

•       Experience with databases, both relational (e.g., PostgreSQL, MySQL) and non-relational (e.g., MongoDB, Redis, Aerospike)

•       Experience building and deploying HTTP-based applications and APIs in production environments

•       Hands-on experience building RAG systems and working with vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant, pgvector)

•       Proven experience developing AI agents using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar

•       Hands-on agentic coding experience (e.g., Claude Code, Cursor, GitHub Copilot Workspace, or similar AI-assisted development tools)

•       Experience with MCP (Model Context Protocol) or similar agent communication standards

•       Strong understanding of prompt engineering, context engineering, and LLM optimization techniques

•       Experience with modern LLM APIs (OpenAI, Anthropic, Google, open-source models)

•       Excellent communication skills with the ability to explain complex AI concepts to technical and non-technical audiences

•       Demonstrated ability to work cross-functionally and drive alignment across teams

Nice to Have:

•       Background in adtech or real-time bidding systems

•       Familiarity with MLOps practices and model deployment pipelines

•       Contributions to open-source AI projects or active participation in AI communities

Why Join Us:

•       Build complex AI systems from scratch that directly impact company-wide performance

•       Work with the latest AI technologies and shape how the organization adopts them

•       High visibility role with direct collaboration across all business units

•       Join a small, agile team where your contributions have outsized impact

•       Hybrid work environment with flexibility

Benefits:

• Competitive compensation package
• International work environment
• Flexible working schedule and the possibility to work remotely
• Annual performance bonus
• English classes
• Maternity/Paternity leave

Langate is an award‑winning provider of web development services in 3 main categories: business, healthcare, and education. At Langate, we're passionate about crafting digital solutions that make a real impact. We take immense pride in our strong collaboration with the U.S. We're here to shape the future of technology, one milestone at a time. In addition to technical expertise, we value excellent communication skills. Collaboration and effective teamwork are the cornerstones of our success, and we believe in fostering an environment where everyone’s voice is heard and valued. To thrive in this role, we’re seeking candidates with a strong academic background and hands‑on experience through pet projects, university work, hackathons, Kaggle, or research, coupled with a solid foundation in Python, ML basics, algorithms, and engineering tools. 

About the project: This internship gives you hands‑on experience working on real AI/ML tasks in a live engineering environment. You will help build and refine ML pipelines, prepare data, run experiments, and evaluate models under the guidance of a mentor. The work includes creating small prototypes, integrating models into simple internal tools, and documenting results. You’ll gain practical exposure to applied AI development and gradually take ownership of small but meaningful components as you learn. Upon successful completion of the internship, there is an opportunity to receive a permanent position within the company. 

Requirements:  

• Strong Python programming skills (required)
• Basic OOP, clean code habits
• Good understanding of data structures & algorithms
• ML fundamentals: supervised learning, train/val/test splits, metrics, overfitting
• Familiarity with PyTorch
• Experience with Git, Linux/CLI, virtual environments
• Data skills: pandas, NumPy, preprocessing 

Nice‑to‑have: 

• Experience with LLMs, Transformers, embeddings, vector DBs (RAG)
• Basic backend/API development (FastAPI/Flask)
• Docker
• Cloud basics (AWS/GCP/Azure) 

 
Responsibilities:

• Implement and improve AI/ML features under mentor guidance
• Run experiments, track results, compare approaches
• Perform model evaluation and propose improvements
• Work on data tasks (cleaning, preprocessing, dataset creation, labeling support)
• Build supporting components (scripts/services)
• Integrate models into simple APIs or internal tools
• Document findings and maintain reproducible code
• Deliver prototypes, experiment reports, feature increments, and clean PRs 

Team: You will be working directly with a mentor and collaborating with an experienced engineering team. Regular syncs: 2–3 times per week (standup/demo/check‑in); rest async. 

Schedule: 6+ hours/day, preferred overlap: 3–5 hours with EET/EEST (UTC+2 / UTC+3). Internship duration: 2+ months, extendable based on performance 

Hiring process: HR interview + tech specialists   

Why Choose Us? What Do We Offer that's Exceptional?    

1. Cutting-Edge Technologies on Real Projects: At Langate, you'll work with the latest technologies on live projects. We're a dynamic, fast-growing company, so you'll find a minimal amount of legacy systems and plenty of opportunities to implement new technologies.
2. Work-Life Balance with Benefits: We value work-life balance and offer paid time off, including vacation days and sick leave. Remote work options and hearty life are part of the package too.    
3. Investment in Your Growth: We're committed to your professional development. You can expect training programs, courses, and opportunities to enhance your English language skills.   
4. Team Building and Unity: We know that a happy team is a productive team. That's why we organize team-building events and group activities to foster strong bonds and a sense of belonging.    

When you choose us, you're choosing a company that values innovation, invests in its employees, and provides a supportive and engaging work environment. Join us in shaping the future of technology!  

Need more information? Welcome! 

We’re looking for experienced AI Engineers to build, deploy, and own production-grade AI systems. This is not a research-only role and not a junior position — we need people who have already shipped LLM-based solutions into real environments, where reliability, performance, and correctness actually matter.

Responsibilities

• Design, build, and deploy LLM-based systems into production environments
• Own end-to-end AI pipelines: experimentation, evaluation, deployment, and maintenance
• Build APIs and services for AI features using FastAPI or similar frameworks
• Implement and maintain RAG pipelines, agent-based systems, and orchestration logic
• Work closely with product and engineering teams to turn vague problems into reliable AI solutions
• Ensure production readiness: scalability, latency, observability, and failure handling
• Take responsibility for systems where errors have real consequences (business, legal, or safety-related)

Requirements

• Strong experience deploying LLMs in real production systems
• Ability to work independently without hand-holding
• Solid Python engineering skills
• Experience with PyTorch and modern LLM tooling
• Hands-on experience with Docker and production APIs (FastAPI or equivalent)

• Deep understanding of what “production-ready” actually means (monitoring, retries, edge cases, costs)

   

Nice to Have / Extra Credit

• Experience with ML infrastructure and model serving at scale
• Background in startups or contract-based engineering environments
• Experience in regulated or high-stakes domains (healthcare, finance, AI safety)
• Knowledge of Rust and/or C++
• Experience with reinforcement learning or multi-agent systems
• Experience designing systems where correctness and robustness are critical

Location: Remote

Type: Full-Time

Department: Engineering / Data Sciencej / AI

We are a company based in California seeking a versatile Generative AI Engineer who sits at the intersection of software development and creative AI. You will not only generate and test high-quality AI imagery but also build and maintain the Python-based tooling that powers our workflows.

Our product is a cutting-edge AI tool that makes children the starts of their own custom stories. We have partnerships with some of the biggest entertainment companies in the world.

Most of our team is Ukrainian.

Key Responsibilities

• Tool Development & Maintenance:
  • Maintain and improve our internal Python-based applications that generate images based on specific prompts.
  • Debug and enhance code in Jupyter Notebooks and manage version control via GitHub.
  • Ensure smooth operation of tools through the Command Line Interface (CLI).
• Image Generation & Workflow Testing:
  • Execute image generation tasks using SwarmUI (training provided, but aptitude required).
  • Run rigorous testing on image outputs to ensure consistency and quality.
• Prompt Engineering:
  • Write, test, and validate prompts to achieve specific visual results.
  • Iterate on prompt strategies to improve the reliability of image models.
• Collaboration:
  • Work closely with key stakeholders to interpret requirements and translate them into technical execution, mostly around efficient and effective prompting as it relates to high-quality images.
  • Communicate technical constraints and wins to cross-functional teams.

Required Qualifications (The "Must-Haves")

• Python Proficiency (Mid-Level): You can write clean functions, debug existing code, and are comfortable working within Jupyter Notebooks.
• Command Line Confidence: You are comfortable navigating the OS, running scripts, and managing environments via CLI.
• Version Control: Standard proficiency with Git and GitHub (pull, push, merge, resolve conflicts).
• Prompt Engineering Basics: You understand how to structure a text prompt to get a desired image result and how to troubleshoot when the model hallucinates or fails.
• Language Skills: Strong professional English (written and verbal) is mandatory for communicating complex requirements with the team.

Preferred Qualifications (The "Nice-to-Haves")

• SwarmUI Experience: Familiarity with this specific interface or similar Stable Diffusion web UIs (ComfyUI, A1111).
• Cloud Autonomy: Experience setting up and managing cloud instances (AWS, GCP, or Lambda Labs) for GPU computing.
• Model Training: Experience training LoRAs, Dreambooth, or fine-tuning checkpoints.
• SOTA Knowledge: A genuine interest in the latest developments in Image Generation (Flux, SDXL, ControlNets, etc.).

Soft Skills & Cultural Fit

• High Autonomy: You don’t need to be micro-managed. If you see a bug in the tool or a way to optimize the prompt workflow, you fix it or propose a solution.
• Bridge Builder: You can act as a translator between technical code and creative visual requests.
• Fast Learner: You can pick up new tools (like SwarmUI) with a short learning curve.

About the project

The client is building a B2B marketplace for surplus inventory that helps businesses reduce waste and improve supply-chain efficiency. The product operates at the intersection of pricing, supply, and demand, and market intelligence, where Machine Learning is a core competitive advantage. This is an early-stage product with no legacy code, a modern tech stack, and close collaboration with the founders. Machine Learning here is not a supporting function but a foundation of the platform’s business logic and growth.

Your area of responsibility

• Designing and building the ML and data architecture from scratch, aligned with business goals;
• Developing pricing, demand forecasting, and optimization models for a B2B marketplace;
• Translating supply-and-demand challenges into scalable ML solutions;
• Defining data collection, feature engineering, and model evaluation approaches;
• Deploying, monitoring, and iterating on models in a production environment;

• Collaborating closely with founders to shape the ML roadmap and long-term strategy.

   

Skills and requirements

• 5+ years of experience in Machine Learning and/or Software Engineering, with a proven track record of delivering ML solutions to production;
• Strong Python skills and hands-on experience with classical ML frameworks (scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow);
• Solid understanding of pricing-related domains: regression models, time-series forecasting, econometrics, or optimization techniques;
• Experience designing end-to-end ML pipelines, from data collection and feature engineering to deployment and monitoring;
• Strong SQL skills and experience working with cloud-based data platforms (PostgreSQL / Supabase is a plus);
• Ability to work independently in ambiguous, early-stage environments and translate business goals into technical solutions.

Will be a plus

• Previous experience in B2B marketplaces, e-commerce pricing, or fintech products;
• Ability to work beyond ML tasks, including tweaking backend APIs or writing SQL functions to retrieve and prepare data;
• Hands-on experience with MLOps tools and practices, such as Docker, Airflow, or specialized frameworks like ZenML or BentoML.

We offer

• Working in a team of talented and passionate engineers;
• Opportunity to work with the most trending technologies;
• Long-term enjoyable cooperation;
• Personal legal support;
• English classes;
• Paid vacation and sick days;
• Competitive salary depending on your own talents;
• Regular performance & career development reviews;
• Team building events.

Our client is building AI-powered solutions that help legal teams automate contract workflows, accelerate deal execution, and improve operational efficiency.
This role combines legal domain expertise with hands-on work on AI-driven automation tools for enterprise customers.

🧩 Responsibilities:

• Design and configure AI agents for legal workflows (intake, contract review, approvals)
• Implement and deploy solutions end-to-end for enterprise clients
• Gather and analyze customer requirements, design workflows, and ensure successful onboarding
• Advise legal, legal operations, and procurement teams on process automation and compliance
• Collaborate with Product and Engineering teams to improve AI agents and workflows
• Train customer teams and support adoption of legal automation solutions
• Work closely with Sales, Customer Success, and Legal stakeholders to deliver measurable results

✅ Requirements:

• 1+ year of experience implementing legal tools (e.g. SimpleLegal, Ironclad, LinkSquares, or similar)
• Upper-intermediate English level (or higher)
• Strong understanding of legal processes, contract lifecycle management, and stakeholder dynamics
• Ability to communicate effectively with legal, procurement, and business teams
• Technical curiosity and readiness to work with AI-based solutions
• Experience working in fast-paced, ambiguous environments
  
  ⭐ Nice to have:
  • Experience with CLM systems and redlining workflows
  • Background in legal automation platforms
  • Technical education or strong technical fluency (CS, Engineering, Math)

We offer:

• Opportunity to work with AI-driven legal technology
• Training in AI agents and legal automation (no prior AI experience required)
• High-impact role with enterprise customers
• Collaboration with cross-functional international teams

We’re building an AI platform that helps businesses automate customer interactions and internal workflows using LLM-powered conversational agents. The product focuses on high-quality, controllable AI behavior: reliable conversations, tool usage (calling internal systems), measurable performance, and fast iteration based on real user feedback.
You’ll work closely with an AI automation expert to bring assistants into real business processes - not demos.

What you’ll do

• Craft, test, and optimize prompts for LLMs to solve real product and business tasks
• Build and refine conversational agents (text and optionally voice) using an internal no-code/low-code tool
• Translate feature requirements into working agent behaviors: flows, guardrails, tone, and structured outputs
• Analyze model responses, run experiments, and iterate based on metrics and feedback
• Maintain a prompt/agent knowledge base, best practices, and reusable templates
• Collaborate with product, engineering, and automation teams to integrate AI into workflows
• Research and evaluate new models and techniques, recommending what’s worth adopting

Requirements (must-have)

• 2+ years of hands-on experience in Prompt Engineering or building LLM-based conversational experiences
• Practical experience with LLM prompting in production-like scenarios (quality, consistency, edge cases)
• Strong analytical thinking: ability to evaluate outputs and improve them systematically
• Solid communication skills and ability to work cross-functionally
• English: B2+ (C1 is a strong advantage)

Nice to have

• Basic Python and experience with LLM APIs (OpenAI, Gemini, Claude, Cohere, etc.)
• Understanding of RAG, structured outputs (JSON/function calling), and evaluation approaches
• Experience building LLM agents (tool calling, multi-step workflows) with LangChain/LangGraph/AutoGen/CrewAI
• Exposure to open-source model ecosystems and practical optimization (e.g., lightweight fine-tuning like LoRA)
• Background in linguistics, media, content creation, or UX writing (we value language craftsmanship)

Why this role

• Real impact: you’ll build AI behavior that users interact with daily
• Ownership of the “AI layer” as a product surface: quality, reliability, iteration speed
• A practical environment focused on shipping, measuring, and improving - not hype

About the Role We are looking for a Senior MLOps Architect to lead high-stakes AI and Data projects for our enterprise customers. In this role, you will act as the technical authority, helping clients bridge the gap between experimental data science and production-grade operations primarily on Google Cloud Platform. You will lead projects that involve building end-to-end MLOps pipelines from scratch, migrating workloads to Vertex AI, and standardizing model deployment. You will usually act as the "trusted advisor" owning the architecture and the delivery. 

Key Responsibilities 

● Customer Leadership: Lead technical kickoffs, discovery workshops, and architecture reviews directly with client CTOs, VP R&D, and Data Science leads. 

● Architecture & Design: Design robust, scalable MLOps architectures using Google Cloud Platform services (Vertex AI, GKE, BigQuery, Cloud Build, Cloud Storage). 

● Implementation & Automation: Build "Golden Paths" for model deployment. Implement CI/CD pipelines for ML, automated retraining workflows, and model monitoring systems to allow Data Scientists to deploy self-sufficiently. 

● Production Engineering: Operationalize ML models in high-scale environments. Troubleshoot complex infrastructure issues (e.g., GPU provisioning, container orchestration, scaling strategies). 

● Strategic Advisory: Advise customers on best practices for MLOps maturity, cost optimization (FinOps for AI), and data governance. Requirements (Must Have) 

● MLOps Experience: At least 3+ years specialized in MLOps and building production ML pipelines. 

● Google Cloud Expert: Deep, hands-on experience with GCP core services (Compute Engine, GKE, IAM, Networking) and specifically Vertex AI (Pipelines, Feature Store, Model Registry).

● Customer-Facing Skills: Proven ability to lead projects, manage stakeholders, and explain complex technical concepts to clients. 

● Containerization & Orchestration: Strong proficiency with Docker and Kubernetes (GKE). 

● Coding: Strong proficiency in Python and SQL. 

● CI/CD for ML: Experience implementing pipelines using tools like Cloud Build, GitHub Actions, or Jenkins. Big Advantage (Nice to Have) ● Databricks Expertise: Experience with the Databricks Lakehouse platform, Unity Catalog, and MLflow is a major plus. Many of our clients use Databricks alongside GCP, so this skill will be highly valued. 

● Certifications: Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect. 

● GenAI Experience: Experience deploying Large Language Models (LLMs) or working with Gemini/Claude APIs in production.

Remote AI Vibe Developer

Open-Source LLM Training & Agentic Product Engineering (Remote)

Role Summary

We’re hiring an AI Vibe Developer — a product-minded engineer who ships production-quality software quickly by combining strong engineering fundamentals with AI-assisted (“vibe coding”) workflows and modern LLMOps best practices (evals, tracing, guardrails, prompt/version management).

A core requirement of this role is working with an open-source / open-weights LLM that we will fine-tune and run ourselves. You’ll help take it end-to-end — from data → training → evaluation → serving → iteration — and integrate it into real, user-facing product flows.

Responsibilities

1) Build & ship AI-powered product features (end-to-end)

• Deliver features from prototype to production: UI, backend, integrations, deployments, and iteration.
• Use AI coding tools/agents to accelerate delivery while maintaining code quality (tests, reviews, standards).
• Own rollout strategy: feature flags, staged releases, rollback plans, and production support.

2) Design agentic workflows and “AI inside” capabilities

• Implement LLM features such as:
  • Tool/function calling with strict schemas and reliable fallbacks.
  • Retrieval-Augmented Generation (RAG) when needed (grounding, freshness, controllable outputs).
  • Multi-step agent flows (routing, planner/executor patterns, memory/context strategies).
• Integrate external tools/services securely (internal APIs, CMS, analytics, ticketing, CRM, etc.).

3) Open-source LLM training & lifecycle ownership

• Help select the best open-weights model baseline based on quality, licensing, latency, context length, and multilingual support.
• Build and maintain the data pipeline: collection, cleaning, de-duplication, PII redaction, formatting, and dataset versioning.
• Run fine-tuning workflows (e.g., SFT and preference tuning when relevant) with reproducibility and experiment tracking.
• Build a practical evaluation suite (golden sets + edge/adversarial cases) to gate training runs and releases.
• Drive iterative improvement using an error taxonomy: failures → targeted data improvements → retrain → regression checks → release notes.

4) Inference, serving, and performance optimization

• Package and deploy the model for production serving (containerized) with reliability and observability.
• Optimize serving latency/cost via batching, caching, quantization, and safe model routing where applicable.
• Implement system-level guardrails: schema-constrained outputs, input validation, tool allowlists, rate limits, and safe degradation paths.

5) Evals-first development and observability

• Define success metrics (quality, groundedness, refusal behavior, latency, cost, user satisfaction) and track them continuously.
• Instrument LLM flows with tracing (inputs, tool calls, retrieved docs, outputs, model/version, latency, cost).
• Maintain prompt/version control and changelogs; support A/B tests and controlled rollouts.

6) Collaboration & enablement

• Work closely with Product, Design, Data, and QA to translate “vibes” into measurable outcomes.
• Create lightweight playbooks: eval templates, prompt guidelines, incident runbooks, and “how we build with AI here.”
• Improve team velocity by sharing patterns and avoiding AI productivity pitfalls (over-trusting outputs, under-testing).
•  

Requirements

Core Engineering

• 3+ years of software engineering experience (or an equivalent portfolio of shipped products).
• Strong proficiency in Python (required for the training stack), plus at least one of: TypeScript/Node.js, Go, or Java.
• Strong fundamentals: API design, async workflows, testing strategy, debugging, CI/CD, Git, and production ownership.

Open-Source LLM Engineering (Must-have)

• Hands-on experience fine-tuning and/or deploying open-weights LLMs end-to-end: data → training → evaluation → serving.
• Strong understanding of:
  • Tokenization and context budgeting
  • Dataset quality, leakage risks, and evaluation methodology
  • Instruction tuning concepts and preference optimization fundamentals

3Shape develops 3D scanners and software solutions that enable dental and hearing professionals to treat more people, more effectively. Our products are market leading innovative solutions that make a real difference in the lives of both patients and dental professionals around the world.

3Shape is headquartered in Copenhagen, with development teams in Denmark, Ukraine, North Macedonia and with a production site in Poland.

We are a global company with presence in Europe, Asia and the Americas. Founded in a year 2000, today, we provide services to customers in over 130 countries. Our growing talent pool of over 2200 employees spans 50 nationalities.

3Shape as an employer is committed to Ukraine. Our UA office was founded in 2006, and we are continuing to grow, hire and take care of our employees even during the war in Ukraine. Among other actions, we support our contractors who are called to the military service, as well as care about our colleagues’ mental health by implementing different activities.

About the role:

As an AI Application Specialist, you will spearhead the technical execution of 3Shape’s After Sales AI Strategy, transforming how we support thousands of dental clinics worldwide. You will bridge the gap between business needs and technical implementation, working closely with the AI Business Owner to design and build high-impact solutions. This is a role for a builder who wants a seat at the table. Beyond execution, you can also play an active role in shaping our AI strategy, directly influencing how we adopt and scale next-gen AI paradigms.

Your key responsibilities will be:

• AI Integration: Lead the integration of external AI tools, ensuring every solution delivers measurable business impact.
• Agentic Systems: Design, test, and productionize sophisticated chat and voice agents featuring LLM reasoning and TTS integration.
• Scalable Automation: Architect workflows that streamline operations and drive efficiency across the organization.
• End-to-End Ownership: Take full accountability for the lifecycle of a product from initial concept and design to production and maintenance.
• Enablement: Empower internal teams by providing the training needed to maximize the adoption of custom AI solutions.
   

Your profile
What we are hoping you have/are:

Education & Experience:

• 2–4 years of experience in Software Engineering or AI/ML development, with a deep understanding of how to build and maintain scalable systems.
• Proven end-to-end solution ownership. You have a track record of shipping and supporting AI solutions in production.
   

Technical Skills:

• Agentic AI Stack: Deep hands-on experience with Agentic Systems, prompt engineering, tool-use (function calling), and RAG/knowledge-base integration. Knowledge of MCP server protocols would be a plus.
• Engineering: Strong Python skills (FastAPI/Flask). Experience in other coding languages would be a plus.
• Tooling: Familiarity with CX platforms (Genesys), Data environments (Databricks/Palantir), or Voice synthesis (ElevenLabs) would be a plus.
   

Being the part of us means:

• Meaningful work that helps to change the future of dentistry
• Work in a unique professional, friendly and supportive environment
• Constant professional growth and development
• A healthy work-life balance
• Comprehensive benefits incl. 24 working days of annual vacation; medical insurance; paid sick leaves and child sick leaves; maternity and paternity leaves etc
• Breakfasts and lunches in the office
• Good working conditions in a comfortable office in UNIT.City
• A parking lot with free spaces for employees
• Occasional business trips to Western Europe
• Opportunity to become a part of the success that 3Shape has created over the past 25 years.

About us:

Erbis is a thriving tech powerhouse where innovation meets opportunity. We specialize in building cutting-edge software solutions that drive success for businesses worldwide. At Erbis, we don’t just develop software. We create impact. And to do that, we need the best talent in the industry. That’s where you come in.

Requirements:

• At least 1 year of recent hands-on experience in applied AI using Microsoft/Azure technologies
• Proven ability to implement AI solutions for real business problems with measurable ROI
• Experience identifying practical applications of existing generative AI technologies in business contexts
• English level: Upper-Intermediate or above
   

Soft skills:

• Excellent communication skills and ability to collaborate with stakeholders to define AI use cases
• Analytical and business-oriented mindset
• Cross-functional collaboration
• End-to-end ownership
• Proactive problem solving under uncertainty
• Architectural thinking
• Continuous improvement & knowledge sharing

Responsibilities:

• Design, develop, and deploy AI-powered applications using Microsoft and Azure technologies
• Identify and evaluate opportunities for applying generative AI and other AI technologies to real business challenges
• Collaborate with business teams to define AI use cases, success metrics, and ROI
• Build scalable, maintainable, and secure AI solutions within Microsoft stacks
• Stay up-to-date with AI trends and emerging technologies, recommending innovative solutions where applicable
• Document architectures, workflows, and AI models for internal knowledge sharing and handoff

Our perks and benefits:

• Paid Vacation days: 24 working days
• Paid Sick days: 15 working days
• The opportunity to dedicate up to 10% of working hours for self-education and personal development

Location: Remote

Working timezone: Toronto / North America overlap (afternoon → late evening EU time);
Engagement: Full-time, long-term

We’re looking for a versatile and hands-on Machine Learning Engineer to join our client's team and take ownership of ML systems from early research through to real-world deployment. In this role, you’ll work across the full lifecycle - shaping datasets, exploring new approaches, building models, and running them reliably in production. T

his is a good fit if you enjoy fast iteration, practical experimentation, and seeing your work directly influence product outcomes.

Responsibilities:

• ML solution design: Explore, evaluate, and implement machine learning approaches to solve complex product and business challenges using modern model architectures.
• Experimentation workflows: Set up and maintain pipelines that support fast prototyping, testing ideas, and validating assumptions.
• Structured experimentation: Plan, run, and document experiments in a reproducible way, including tuning hyperparameters, comparing architectures, and testing data variants using tools like MLflow or Weights & Biases.
• Production rollout: Bring models into production using established CI/CD workflows and model serving infrastructure.
• Model observability: Build monitoring and alerting around deployed models to track accuracy, drift, latency, and overall system health.
• Inference optimization: Improve runtime performance and cost efficiency through techniques such as quantization, pruning, and distillation.
• Training data ownership: Create, refine, and maintain high-quality datasets, including data augmentation and curation strategies.
• Modern ML methods: Keep up with current advances in the field and apply state-of-the-art approaches, particularly in the area of large language models.

Requirements:

• 3+ years of hands-on experience building and deploying machine learning models in production systems.
• Strong Python skills and experience writing production-grade ML code.
• Solid experience with deep learning frameworks, especially PyTorch.
• Practical background in hyperparameter tuning and optimization using tools such as Optuna or Ray Tune.
• A disciplined approach to experimentation, with strong habits around reproducibility and tracking.
• Hands-on work with LLMs, including fine-tuning, prompt design, retrieval-augmented generation, and efficient inference.
• Experience applying model optimization techniques (e.g. quantization, pruning).
• Proven ability to design and build datasets rather than only consuming existing ones.
• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a closely related field.

Nice to have:

• Experience with advanced architectures such as Transformers or Mixture-of-Experts models.
• Contributions to open-source projects or personal ML projects that demonstrate curiosity and depth.
• Practical understanding of end-to-end MLOps, including tools like Docker, Kubernetes, MLflow, Kubeflow, or Prometheus.

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

1 EM, 5 ML 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 other.
  • Experienced in natural language processing and modern LLM based techniques.
  • Experience with full ML lifecycle, data preprocessing, training, evaluation stages 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 express your thoughts in a professional manner 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 learnings 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.

Про компанію SPD TechnologySPD Technology is a custom software product development and IT consulting company with a world-class team of over 600 experts with extensive expertise in solving big-time technical challenges, efficiently managing large-scale software development efforts, and seamlessly integrating with the client’s business through tailored, long-term partnerships for delivering cutting-edge tech solutions that drive clients' growth.

Our major expertise includes 10 key industries: Fintech, E-commerce, Telecom / IoT, e-Learning, Logistics, Insurance, Biotech, Cybersecurity, Medicine, Wellness. Our top-notch engineering teams deliver Web, Mobile, AI/ML or Enterprise solutions for world-renowned businesses and budding startups. Our key clients are iconic brands such as PitchBook, MorningStar, Roche, and more. Ten of our clients report more than $100 million in annual revenue.

We have 3 development centers in Eastern Europe, and remote teams, working worldwide. With over 17 years of experience in designing, building, streamlining, and supporting software products, SPD Technology drives growth of businesses from the US, the U.K., Israel, Switzerland, Mexico, and other countries.

Let’s create empowering tech solutions together!

Ekreative is purposeful about every decision: how we hire, build long-lasting partnerships with our clients, set our development procedures, and impact social change with our finances. Since the very beginning, Ekreative has been committed to giving away a significant portion of our profit on a monthly basis to various charities, influencing thousands of lives. With over a decade of experience delivering innovative solutions, we’re now investing in AI to enhance both how we work and the value we deliver to our clients.

We are looking for a VP of AI — a visionary and hands-on leader dedicated to driving AI innovation across Ekreative. This is a full-time executive position focused on researching, testing, and integrating emerging AI technologies to elevate our software development capabilities and operational excellence.

The role has two core focuses:

1. Client-Facing Innovation

• Continuously explore and adopt AI technologies that enhance the quality, speed, and competitiveness of Ekreative’s client services
• Drive AI-powered improvements across design, development, testing, and delivery processes
• Collaborate with project teams to identify opportunities for AI integration into client products and services

2.Internal AI Enablement

• Leverage AI to optimize Ekreative’s internal workflows, knowledge management, and decision-making
• Implement and refine AI tools that improve efficiency across operations, HR, sales, and project management

• Foster a culture of AI adoption and continuous learning within the company

   

Key Responsibilities:

• Develop and lead Ekreative’s company-wide AI strategy and roadmap
• Research and evaluate new AI technologies, frameworks, and tools relevant to software development
• Partner with delivery, R&D, and operations teams to pilot and scale AI-driven initiatives
• Identify measurable KPIs and report progress to the executive team
• Build and mentor an internal AI innovation group or guild
• Stay ahead of global AI trends, ensuring Ekreative remains an early adopter in key areas

• Represent Ekreative’s AI expertise in client discussions, marketing, and industry events

   

Requirements:

• 7+ years of experience in software development, data science, or AI leadership, including at least 3 years in a senior or executive-level role
• Proven track record of implementing AI technologies in a commercial software or services environment
• Deep understanding of modern AI tools, platforms, and frameworks (e.g., GenAI, Copilot, Claude, OpenAI, Gemini, LLM fine-tuning, etc.)
• Strong leadership, communication, and stakeholder management skills
• Strategic thinker with the ability to convert emerging technologies into actionable business initiatives

• Experience leading cross-departmental innovation projects and managing technical change

   

We offer:

• Opportunity to shape the AI direction of an established, fast-evolving company
• Collaboration with a talented cross-functional team
• Flexible work environment
• Competitive compensation and long-term growth potential
• Partial reimbursement for medical insurance, sports activities, and English language courses
• Generous leave policy - 22 days of annual leave, 10 paid sick days per year
• Personal equipment policy offering MacBooks along with all necessary hardware and software for work
• Financial support for employees during specific life events (weddings, childbirth, etc)
• A people-focused corporate culture that prioritizes employee well-being

Job Description

• Good knowledge of Python or any other relevant programming experience (e.g. C++);
• Good understanding of Machine Learning techniques;
• Experience with numpy, scipy, opencv, tensorflow (at least some of them);
• Understanding of or experience with Computer Vision and Deep Learning;
• BS or BA degree in a relevant area is a must (e.g. Applied Mathematics, Physics, Computer Science);
• Any kind of commercial experience in software development would be a plus;
• Good communication skills, including at least Pre-Intermediate English level for daily communication.

Job Responsibilities

• Design and develop PoC applications
• Apply AI/Machine Learning technology to solve real problem for market available product

Department/Project Description

Our client runs one of the most popular amusement parks in the world. The safety of their guests and cast members is the key to providing a seamless entertainment experience and our client was looking for ways to leverage the latest technology to take safety to the next level.

GlobalLogic helps the client create a flexible real-time AI-based attraction monitoring system to detect, alert, and record any discrepancy between the number of people detected by an overhead camera and the number of occupied seats from the seat sensor indicator lights.