Jobs ML / AI Engineer

It is a leader in AI-powered computer vision and predictive systems for manufacturers, delivering integrated solutions that connect edge devices and factory systems with cloud software to optimize production quality and throughput. As a Forward Deployed Engineer, you will play a pivotal role in deploying advanced AI systems directly into customer environments, acting as the primary technical contact and trusted advisor for strategic manufacturing accounts.

Key responsibilities include:

• Own the end-to-end lifecycle of AI deployment for manufacturing clients, from scoping and integration to production hardening and handover.
• Embed with customer operations and IT teams, serving as the main technical advisor and point of contact.
• Integrate AI vision systems with OT/IT/cloud stacks, including OPC-UA/Modbus/PLCs, NVIDIA Jetson edge inference, ERP, and customer cloud platforms.
• Build and iterate data pipelines and customer-side data flywheels, covering edge-to-cloud capture, model deployment, monitoring, and feedback loops.
• Troubleshoot software, networking, and integration issues in live production environments.
• Document architectures and configurations, producing formal handover artifacts for long-term support.
• Participate in pre-sales scoping calls and contribute field learnings to the product and engineering roadmap, helping shape reusable deployment patterns and internal tooling.
• Support on-site data collection and annotation as needed.

Requirements
Required Qualifications:

• 6+ years of experience combining production software engineering with industrial automation and/or applied AI
• Proven experience shipping and supporting production software systems deployed into customer infrastructure
• Production Python development experience with hands-on use of Linux, Docker, and Git in production environments
• Cloud deployment and operations experience with at least one major platform (AWS, Azure, or GCP)
• Hands-on experience with at least one of: OPC-UA/Modbus/PLC integration, NVIDIA Jetson (or equivalent) edge platforms, or GenICam/industrial vision systems
• Networking fundamentals for industrial deployments, including TCP/IP, VLANs, and firewalls
• Experience in a customer-facing engineering role as the primary technical contact for external stakeholders
• Professional working proficiency in English

Preferred Qualifications:

• Professional experience working in industrial automation or manufacturing environments involving OT/IT integration

Основні вимоги:

• 6+ years of technical experience
• Python/Linux/Docker - 3+ years
• production deployments or system integration - 3+ years
• industrial automation/factory systems - 2+ years
• PLC/OPC-UA/Modbus or industrial networking - 1–2+ years
• computer vision/Edge AI - 1–2+ years
• client-facing experience - 2+ years

Графік до 01:00 ночі по Київу !!!

Location: Remote (Poland / EU)
Duration: Contract until end of year (with potential extension)

We are looking for a Senior Backend Engineer (Golang) with a strong interest or experience in AI and Large Language Models (LLMs) to join a high-impact project. You will play a key role in designing, building, and optimizing backend services that integrate modern AI capabilities.

This is a senior-level position requiring autonomy, ownership, and the ability to contribute to architectural decisions while collaborating with cross-functional teams.

Key Responsibilities

• Design, develop, and maintain scalable backend services using Golang
• Build and optimize RESTful APIs for high-performance applications
• Collaborate on system architecture and technical design decisions
• Integrate and work with AI/LLM-based solutions and agents
• Ensure code quality, performance, and reliability

• Work independently with minimal onboarding while aligning with broader project goals

   

  Must-Have Requirements

• Strong proficiency in Golang as a primary programming language
• Extensive experience building and maintaining REST APIs
• Hands-on experience with databases such as PostgreSQL, SAP HANA, or similar
• General understanding of AI concepts, especially Large Language Models (LLMs) and AI agents
• Ability to work independently at a senior level
• Nice-to-Have Skills
• Experience with OpenTelemetry (observability, tracing)

• Familiarity with performance and load testing tools (e.g., Locust)

   

  What We’re Looking For

• A senior engineer who can own features end-to-end
• Someone comfortable with high-level architectural discussions
• Ability to collaborate without needing constant direction
• Strong problem-solving mindset and focus on scalable solutions
• Language Requirements
• Professional proficiency in English
• If you're a backend expert with Golang and an interest in AI/LLMs, this is a great opportunity to work on cutting-edge solutions in a flexible, remote environment.

s a Foundry AI Developer, you will be at the forefront of building the “Enterprise Brain” by architecting intelligent systems that bridge the gap between massive data lakes and actionable AI. Your primary objective is to design, develop, and optimize an agentic ecosystem using Microsoft Fabric, Azure AI Search, and the Model Context Protocol (MCP). You will be responsible for creating the “nervous system” that allows LLMs to interact securely with proprietary data and internal tools while maintaining peak performance and cost efficiency.

Key Responsibilities

1. Unified Knowledge Engineering (Fabric & AI Search)
The Focus: Building the "Enterprise Brain" by linking Microsoft Fabric’s OneLake to Azure AI Search / Foundry IQ.
Key Responsibilities:
Developing Fabric Data Agents that serve as live conduits between structured lakehouse data and the Foundry Hub.
Configuring Azure AI Search as a vector-enabled index to ingest unstructured data from Fabric, enabling "Agentic RAG" where the agent decides when to pull deep historical data vs. real-time telemetry.
Implementing Foundry IQ skills to handle semantic chunking and multimodal embeddings, ensuring the LLM receives highly relevant context.
2. Python-Based MCP Server Architecture
The Focus: Creating a secure "Nervous System" that allows LLMs to act on proprietary systems using the Model Context Protocol (MCP).
Key Responsibilities:
Developing custom MCP Servers in Python (using asyncio and FastAPI) to expose private APIs and local tools as "Functions" that the agent can invoke.
Hub Registration: Registering these servers within the Foundry Hub as persistent connections, allowing multiple AI agents to share the same toolsets securely.
Managing identity and access through Foundry Control Plane, ensuring that agent "tool-use" follows enterprise security policies (OAuth/Managed Identities).
3. Model Orchestration & Token Optimization
The Focus: Selecting the "Right Model for the Right Task" to maximize performance while minimizing token burn.
Key Responsibilities:
LLM Evaluation: Using Foundry’s Evaluation Dashboard to run "LLM-as-a-judge" benchmarks, comparing models (e.g., GPT-4o for complex reasoning vs. Phi-3 or Llama 3 for extraction) to find the most cost-effective fit for specific sub-tasks.
Token Efficiency: Designing Python-based "Routing Logic" that sends simple queries to small language models (SLMs) and reserves expensive LLMs for complex orchestration.
Observability: Monitoring "Token Burn" per agent run in the Foundry portal to identify prompt bloat and optimize system instructions for brevity without losing accuracy.

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

We are seeking an experienced AI Edge Device Developer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and optimizing AI algorithms and models for deployment on edge devices. Excellent problem-solving skills, attention to detail, and the ability to work in a fast-paced environment are essential for success in this role. If you are passionate about pushing the boundaries of AI at the edge and thrive in a collaborative environment, we encourage you to apply.
 

About:

Our client is developing electro-mechanical devices for dairy farms, pulsators and automatic detachers. The solution is leading in the industry with advanced cow monitoring solutions based on activity and rumination sensors.

Responsibilities:

• Designing, developing, and optimizing computer vision pipelines for deployment on edge devices;
• Cross-compiling solutions for various CPU/NPU/VPU types. Perform performance analysis and optimization to ensure real-time processing capabilities on edge devices;

• You will face real-life challenges and complexities emerging from working closely with our AI researchers to provide market leading products.

   

Requirements:

• 5+ years experience in Python, C/C++;
• Hands-on experience with GStreamer or DeepStream;
• Experience with TensorRT, ONNX;
• Experience with processing multiple video streams;
• Hand-on experience with ML accelerators, such as: Nvidia Jetson, Google Coral;
• Proficient in Linux;
• Proficient in Git version control;
• Bachelor's Degree in Computer Engineering, Computer Science or related fields;

• At least Upper-Intermediate English level.

   

Would be a plus:

• Understanding of concepts in signal processing, machine learning and computer vision;
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch;
• Neural network models quantization and pruning;
• Familiarity with building Docker images (Docker files);
• Understanding of CI/CD processes for production code, unit tests, and regression testing;

• Knowledge of CUDA.

   

We offer:

Professional Development: Free English courses, free access to the corporate Udemy account, corporate digital library subscription, possibility to participate and share your knowledge as a speaker in our internal meetups.

Benefits: 100% paid vacation and sick leaves, opportunity to accumulate part of the own salary in the company in dollar terms.

Overview
We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied machine learning and data engineering, ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences;

• Stay up to date with recent ML/AI advancements and evaluate promising methods for future implementation.

   

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

Reply.io is a fast-growing SaaS company helping businesses automate and scale their sales outreach.

We're looking for a Prompt Engineer to work with large language models (GPT, Claude, and others) — enhancing their performance through prompt tuning and conducting research using AI coding agents.

This is hands-on, focused prompt work — sometimes repetitive, always precise — with direct impact on how Jason AI and our other AI-powered features perform.

If your success formula is: 👉 Right model + Right prompt structure + Right evaluation + Continuous iteration — you'll thrive here.

🎯 What you'll do:

• Refine existing prompts — continuously improve quality across our AI features, from simple categorisation to complex, highly personalised email sequence generation, including addressing minor bugs in the results
• Develop new prompts for upcoming AI tools and workflows aimed at making customers' work easier and more efficient
• Use AI coding agents to research, prototype, and validate prompt approaches
• Test prompts on newly released models (Claude, GPT, and others) — compare performance, document trade-offs, recommend upgrades
• Partner with sales, growth, and dev teams to make sure AI outputs match real business needs
• Embrace the detail-oriented, sometimes repetitive nature of prompt tuning — consistent quality matters more than novelty here
• Stay ahead of LLM advancements — new models, new techniques, new evaluation methods

🧩 Requirements:

• 0.5–1 year of experience as a Prompt Engineer, understanding of AI agent workflows, or light scripting/development background (will be a plus — candidates without prior experience are also welcome to apply)
• Passion for AI and hands-on experience with LLMs (GPT, Claude, or similar)
• Prompt tuning expertise — you've optimised prompts and can articulate what worked, what didn't, and why
• Attention to detail and patience for focused, methodical iteration — the role involves repetitive refinement with consistent quality
• Strong communication — you can translate between business needs and LLM behaviour, working across sales, growth, and dev teams
• English proficiency (B2+) — written and spoken
• Willingness to learn — you actively follow AI trends and test on new models as they release

🎁 What we offer:

• Ownership of prompts that ship into customer-facing AI features used by sales teams every day
• Work with cutting-edge LLMs — Claude, GPT, and whatever ships next; premium API access covered
• High autonomy — no micromanagement, no bureaucracy, real ownership
• 100% remote with minimal meetings
• Coverage of professional courses, gym memberships, or therapy sessions
• AI-first culture — we actively use and cover costs of premium tools
• 15 paid vacation days, 🇺🇦 national holidays & ~10 days of Christmas vacation
• Sick leaves without limitations
• Access to internal training, literature, and knowledge sessions

If you love prompting, think in iterations, and are excited to shape how Jason AI performs — we'd love to hear from you!

Pozotron is seeking an AI Engineer to join our development team. Our growing development team, based in Ukraine, is dedicated to creating incredible technology for audio production. The AI Engineer will be an instrumental part of our team, focusing on improving functionality, flexibility and performance of our AI tools.

Required:

• 3+ years of experience with Python
• 2+ years of experience with Machine Learning
• 2+ years of experience with Data Analysis
• Experience with NN inference (ONNX, vllm, etc.)
• Experience with multiple facets of LLMs, including fine-tuning, inference, and orchestration
• Experience with agentic AI, including vibe coding. Experience with multiple models preferred.
• Knowledge of Statistics
• Intermediate+ level of English
• Excellent problem-solving skills and attention to details
• Good communication skills

Nice to have:

• Bachelors or Masters degree in Computer Science, Information Technology, Mathematics, Physics or Engineering
• Knowledge of RDBMS
• Experience with Audio and Text processing
• Experience with Django
• Experience with Cython
• Experience with GCP
• Experience with Docker and Kubernetes
• Experience with Linux

We offer:

• Fully remote work
• Competitive compensation, benefits, and bonus plans
• Health insurance

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

AI Agent Engineer 

About the Role

We are looking for a skilled AI Agent Engineer to build advanced AI agents and autonomous workflows powered by modern LLM technologies.

You will work on production-grade agentic systems, orchestration frameworks, memory systems, tool calling, and multi-agent architectures.

This role is ideal for engineers passionate about the future of autonomous AI systems.

Responsibilities

• Develop AI agents and agentic workflows
• Build and optimize multi-agent systems
• Implement RAG pipelines and memory architectures
• Integrate external tools and APIs into AI systems
• Work with orchestration frameworks such as LangGraph, CrewAI, or AutoGen
• Improve reliability, evaluation, and observability of AI systems
• Deploy and maintain production AI applications
• Collaborate with product and engineering teams

Requirements

• 3+ years of software engineering experience
• Hands-on experience with LLM applications and AI agents
• Experience building AI agents or agentic workflows
• Strong Python skills
• Experience with:
  • LangGraph / CrewAI / AutoGen
  • OpenAI APIs
  • RAG systems
  • Vector databases
  • Prompt engineering
  • Tool calling
• Experience deploying production systems
• Understanding of agent memory and orchestration concepts

Nice to Have

• MCP experience
• AI evaluation frameworks
• AI observability tools
• Fine-tuning experience
• Open-source AI contributions
• Personal AI projects / GitHub portfolio

We Offer

• Remote-first environment
• High-impact AI projects
• Modern AI stack and technologies
• International team
• Long-term collaboration

We're hiring a Senior Software Engineer to join us for a long-term engagement with a fast-growing UK travel tech client. The role focuses on owning and evolving their production document AI pipeline (OCR plus ML inference on passport and ID documents, CPU only deployment, no GPU).

This is hands-on production engineering, not research. You'll be improving OCR accuracy, optimizing CPU inference (INT8 quantization, ONNX Runtime, batching), refactoring pipeline complexity, and improving observability of a system serving enterprise clients at scale.

What you'll do:

• Take ownership of the existing OCR and document understanding pipeline in Python
• Optimize ML inference for CPU production (ONNX Runtime, quantization, batching, kernel tuning)
• Improve OCR accuracy, latency, throughput, and memory efficiency
• Refactor architectural complexity and reduce technical debt
• Work across ML systems, backend services, APIs, and data pipelines
• Help shape architectural decisions as the platform scales

Required:

• 5 plus years of professional Python software engineering
• Strong experience with OCR and document processing pipelines
• Familiarity with LayoutLMv3, Doctr, PaddleOCR, EasyOCR, Donut, or DocFormer
• Production ML systems experience (not just notebook experimentation)
• ONNX Runtime, quantization, TorchScript, or related CPU inference optimization
• Strong understanding of PDFs, image preprocessing, bounding boxes, and page segmentation
• Experience with systems serving external customers at scale

Nice to have:

• HuggingFace Transformers production experience
• Enterprise SaaS or aviation/travel tech background
• MLflow, Vertex AI, or similar ML operations tooling
• Distributed systems and backend API design experience

Engagement:

• Fully remote
• Long-term (6 plus months) with potential to expand engineering ownership over time
• Part-time (25-30 hrs/week) or full-time (35-40 hrs/week), depending on candidate availability
• Flexible timezone (engagement requires some overlap with UK working hours)

How to apply:
Send a short note covering relevant OCR / document AI work, production ML systems you've shipped, CPU inference optimization experience, GitHub or LinkedIn, current availability, and timezone.

Are you passionate about building intelligent systems that can think, act, and adapt? At Sigma Software, we work on innovative AI-driven solutions that push the boundaries of technology. In this role, you will design, build, and optimize cutting-edge AI deployment systems — from autonomous agents to complex orchestration layers — for both greenfield products and established platforms.

We are seeking a highly skilled AI Deployment Engineer to lead the implementation of advanced AI solutions in operational environments. This role requires strong customer-facing presence, exceptional advisory skills, and the ability to design and deploy AI systems that deliver measurable organizational impact.

Requirements

• Proven experience in AI/ML deployment and system engineering.
• Strong proficiency in AI frameworks.
• Expertise in large language models, retrieval-augmented generation, and AI agents.

• Excellent communication and stakeholder management skills.

   

  Responsibilities

• Collaborate directly with customers, providing strategic guidance and technical expertise.
• Own the vision for AI operations implementation, building end-to-end workflows and taking them to production.
• Translate complex business challenges into actionable technical plans.
• Rapidly prototype AI solutions to demonstrate possibilities to clients.
• Engineer production-grade AI solutions with deep knowledge of AI tooling, architecture, and deployment.
• Manage stakeholder alignment, proactively escalating issues and requesting support when necessary.
• Design and build LLM workflows, RAG pipelines, agentic systems, and custom data pipelines.

We’re on the hunt for a talented AI/ML Engineer to design, implement, and optimize cutting-edge AI/ML solutions. If you thrive on solving complex problems and creating production-ready models, we’d love to hear from you!

.  What You’ll Do:

• Develop and fine-tune AI/ML models for performance and scalability.
• Enhance production models, debug issues, and ensure reliability.
• Work with cross-functional teams to shape future AI/ML innovations.
• Explore emerging AI/ML technologies and recommend tools/frameworks.
• Build robust pipelines using Python, SQL, Docker, and more.

.  What We’re Looking For:

• Strong experience in AI/ML, data science, or data engineering.
• Expertise in Python, TensorFlow, Keras, Scikit-learn, and Generative AI.
• Familiarity with Docker, Streamlit, and data tools like Pandas and SQL.
• Strong communication skills and the ability to work independently.

• English: Upper-intermediate or higher.

   

  What We Offer:

✔️ 18 vacation days + 12 sick leaves annually.
✔️ A high-tech workplace (MacBook Pro + Dell monitor).
✔️ Exciting projects with cutting-edge technologies.
✔️ Flexible work hours and competitive salary.
 

Ready to shape the future of AI/ML with us? 🚀 Apply now and be part of something extraordinary!

You will work on scalable AI solutions, developer-focused tools, workflow automation, and AI capabilities that improve engineering productivity and deliver real business value for clients.
 

Responsibilities:

— Design, build, and deploy LLM-based applications and agentic AI systems from prototype to production.

— Develop production-grade AI agents, multi-agent systems, and tool-using workflows.

— Implement RAG pipelines over proprietary and third-party data sources.

— Build and maintain vector databases for AI data storage, retrieval, and search.

— Design and implement AI-powered capabilities such as code assistance, documentation generation, test automation, summarization, knowledge discovery, and code review support.

— Evaluate foundation models such as OpenAI, Anthropic, Gemini, Llama, and other commercial or open-weight models.

— Build LLM evaluation and benchmarking pipelines, including offline tests, online monitoring, human-in-the-loop review, and quality measurement.

— Improve model performance across relevance, faithfulness, latency, throughput, reliability, and cost.

— Design and maintain APIs, backend services, integrations, data flows, and custom tools for AI systems.

— Build custom tools, skills, integrations, and MCP-style server/client patterns for agentic workflows.

— Deploy, monitor, and optimize AI systems on cloud platforms, with a focus on scalability, reliability, observability, and cost efficiency.

— Collaborate with solution architects, engineers, product stakeholders, and delivery teams to translate business problems into technical solutions.

— Participate in architecture discussions, code reviews, design reviews, and technical decision-making.

— Troubleshoot production issues, system bottlenecks, and AI performance problems.

— Document system designs, development processes, technical decisions, and best practices.

— Mentor other engineers and help improve engineering quality across the team.

— Stay up to date with the fast-moving AI, LLM, and agentic AI landscape.

Requirements

— 2+ years of hands-on experience building and deploying LLM-based applications, RAG systems, or AI agents in production.

— Strong software engineering fundamentals and ability to write clean, maintainable, production-ready code.

— Strong Python experience, ideally 3+ years.

— Experience building backend systems, APIs, services, integrations, and data flows.

— Experience with object-oriented programming, backend architecture, design patterns, and production system design.

— Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.

— Strong experience designing agentic AI systems, tool-using agents, or multi-step AI workflows.

— Experience with RAG architecture, including chunking strategies, embeddings, vector databases, reranking, and retrieval evaluation.

— Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, Milvus, or similar.

— Experience with LLM evaluation and benchmarking, including designing evaluation pipelines and measuring model performance.

— Strong prompt design, prompt iteration, and prompt optimization skills.

— Experience working with major model providers or open-weight models such as OpenAI, Anthropic, Gemini, Llama, or similar.

— Cloud experience with AWS, GCP Vertex AI, Azure AI Foundry, or similar platforms.

— Experience with production testing, observability, monitoring, performance optimization, and cost optimization.

— Solid understanding of algorithms, data structures, machine learning concepts, and data engineering fundamentals.

— Familiarity with AI safety, responsible AI, guardrails, and output validation for production systems.

— Experience with CI/CD pipelines, deployment workflows, and engineering best practices.

— Strong problem-solving, analytical, collaboration, and communication skills.

We offer:
— remote time job, B2B contract
— 12 sick leaves and 18 paid vacation business days per year
— Comfortable work conditions (including MacBook Pro)
— Smart environment
— Interesting projects from renowned clients
— Competitive salary according to the qualifications
 

About Us

Our client is MilTech startup building an on-premises platform for automated annotation of UAV video and training computer vision models for autonomous flight.

We have a strategic partnership with one of the largest Ukrainian UAV manufacturers and access to what is likely the largest privately owned UAV video dataset in the world.

The company is at a very early stage — the funding is secured, the technical vision exists, and the data is available. Our focus now is building the core engineering team to turn this platform into reality.

The Role

We are looking for a Lead Computer Vision / Machine Learning Engineer to join as a founding member of the engineering team.

This role is highly hands-on and strategic. You will define the ML architecture, select the tools and frameworks, and build the machine learning pipeline from the ground up. As the platform grows, you will also build and lead a team of ML engineers.

While the high-level technical direction is defined — including petabyte-scale video processing, active learning pipelines, and edge deployment on NVIDIA Jetson devices — the implementation details will be driven by your expertise and technical judgement.

Responsibilities ML Architecture & Technical Direction

• Design and implement the end-to-end ML pipeline, from raw video ingestion to model deployment on UAV hardware
• Evaluate and select appropriate frameworks and infrastructure tools
• Build systems for experiment tracking, model versioning, and reproducible training
• Establish the training infrastructure and ML development workflow
• Make strategic build vs. integrate decisions across the ML stack

Data Pipeline & Curation

• Design video preprocessing pipelines including:
   
  • clip segmentation
  • frame extraction
  • scene detection
  • embedding generation
• Develop data curation workflows to extract high-quality training datasets from large-scale raw video
• Define the annotation ontology and labeling standards for detection, classification, segmentation, and multi-object tracking

Model Development

• Train and improve computer vision models for:
   
  • object detection
  • scene classification
  • object tracking
  • segmentation
• Implement distributed multi-GPU training for large-scale experiments
• Design and implement active learning pipelines including:
   
  • automated labeling
  • confidence-based routing
  • human review workflows
  • retraining triggers
• Define model evaluation metrics and promotion criteria

Edge Deployment

• Optimize models for real-time inference on NVIDIA Jetson hardware
• Implement model optimization techniques including:
  • ONNX conversion
  • TensorRT acceleration
  • INT8 quantization
• Design the model delivery pipeline from training registry to deployed UAV systems

Team Building

• Hire and mentor ML engineers as the team grows
• Establish engineering practices including:
  • code review
  • testing standards
  • documentation
• Own and communicate the ML technical roadmap

RequirementsMust Have

• 5+ years of experience in computer vision and deep learning, including production deployments
• Strong proficiency with PyTorch, including distributed training
• Experience building object detection and tracking pipelines (YOLO, RT-DETR, Detectron2, or similar)
• Experience optimizing models for edge or mobile deployment (TensorRT, ONNX, SNPE, or similar)
• Experience building ML infrastructure and training pipelines
• Strong Python skills and ability to write production-quality code
• Experience leading or mentoring engineers

Nice to Have

• Experience with UAV, drone, robotics, or autonomous systems
• Experience deploying models on NVIDIA Jetson
• Experience with high-performance video processing pipelines (DeepStream or custom)
• Experience in defense or MilTech environments
• Experience defining ML architecture from scratch in early-stage startups
• C++ experience for performance-critical components

What We Offer

• Founding engineering role with direct influence on company technology
• Ownership of the entire ML pipeline from raw data to deployed models
• Access to one of the largest privately owned UAV video datasets in the world
• Dedicated on-prem GPU infrastructure
• Open-source-first engineering approach
• Opportunity to build and lead a machine learning team
• Competitive salary
• Stock options