Jobs ML / AI Engineer

We are looking for an AI/ML Research Scientist.

Requirements:

• PhD with 1+ years of research experience in Electrical Engineering, Computer Science, Information Systems, or a STEM-related field
• 1+ years of experience with modern machine learning architectures including Transformers, Graph Neural Networks, and Diffusion models
• Strong coding skills in Python and C++
• Experience with machine learning frameworks like PyTorch
• At least 1 publication in top machine learning conferences (NeurIPS, ICML, ICLR, etc.)
• Experience with deep learning on graphs (general graphs, circuit graphs, molecular graphs, or trees)
• Familiarity with classical search and optimization techniques (Genetic Algorithms, Monte-Carlo Tree Search, Dijkstra's Algorithm, etc.)
• Experience with EDA tools, either commercial or open-source
• Publications in top-tier venues focusing on AI for chip design or AI for materials science. 

ML Engineer / MLOps Engineer

Location: Remote
Duration: Long-term
 

Основні обов'язки:

• Керувати повним циклом розгортання, підтримки та моніторингу ML/DL-моделей у production.
• Проєктувати та впроваджувати системи керування датасетами та лейблами, включаючи versioning та інтеграцію customer feedback.
• Розвивати Model Registry з підтримкою версіонування, model lineage та локального inference.
• Впроваджувати рішення для Experiment Tracking та Monitoring (ML та Generative AI), включаючи оцінку моделей, виявлення data drift та забезпечення відтворюваності експериментів.
• Розвивати системи model serving та inference: autoscaling, A/B testing, canary deployments, оптимізація latency та вартості.
• Забезпечувати інфраструктуру для Generative AI (prompt management, tagging tools, LLM testing).
• Покращувати DevOps-процеси, автоматизувати ML workflows та впроваджувати reusable компоненти (CI/CD, data loaders, automated retraining).
• Тісно співпрацювати з Data Scientists та командою Data Platform Engineering для впровадження ML-рішень у production.
   

Основні вимоги:

• Вища освіта у сфері Computer Science, Software Engineering або суміжній галузі.
• Практичний досвід роботи як ML Engineer та MLOps Engineer.
• Глибоке розуміння ML/DL workflows та MLOps best practices.
• Досвід побудови та підтримки CI/CD процесів.
• Комерційний досвід роботи з AWS, Azure або GCP.
• Впевнене володіння Python та Java.
• Досвід роботи з PostgreSQL, MongoDB, Redis.
• Практичний досвід з MLflow, Langfuse, SageMaker або аналогічними інструментами.
• Досвід роботи зі Spark.
• Досвід використання PyTorch або TensorFlow.
   

Важливо:  мати комерційний досвід одночасно як ML Engineer, так і MLOps Engineer.

Interview Process:
1. HR with Recruiter (~30 min)

2. GenAI Avatar Screening  (~30 min)

3. Intro call with the client (~30 min)
4. Technical interview (~2 hours)
5. Second technical interview (1–1.5 hours)
6. Final HR interview with client (~30 min)

About QOVES
QOVES is a technology company pioneering facial aesthetics, helping consumers make smarter beauty decisions. Every day, people make important decisions about their appearance based on guesswork or generic advice. We help them decide with clarity instead. Our platform gives customers a clear, science-backed understanding of their face, paired with bespoke advice on how they can look better. Our work reaches millions: more than 2.5 million people follow QOVES across platforms and most importantly, our customers are delighted, with 4.8 stars across 600+ reviews; we believe this reflects the care and sensitivity with which we approach everyone who comes to us for guidance. We're a profitable, growing company headquartered in London, with a team across the globe. What guides us is simple: people deserve more than one-size-fits-all advice when it comes to their appearance. Every decision we make (from the science behind our models to the way we communicate results) is grounded in evidence, responsibility, and a broad, inclusive understanding of beauty.

About the Role
You will join the backend team building the computer vision and machine learning systems that power QOVES's facial analysis platform. The non-negotiable is proven production experience: at least 3 years building scalable software in Python, with hands-on work shipping AI or ML features, including computer vision or LLM-based systems, into a live codebase. You will work closely with the AI Research team to translate research prototypes into production-ready code, own delivery end to end across analysis, design, coding, testing, deployment, and support, and optimise applications for performance and scalability as usage grows. You will also work with the wider team to spot problems early and resolve them before they become blockers.

What We're Looking For
• 3+ years of professional experience in production-level scalable software development with Python
• Strong proficiency with Python for building production-grade APIs
• Hands-on experience integrating AI or ML features, including computer vision or LLM-based systems
• Solid grasp of software architecture principles and API design, with the ability to contribute meaningfully to architectural decisions
• Experience owning work across the full software development lifecycle
• Strong sense of code quality, testing discipline, and engineering best practices
• Excellent communication skills, with the ability to articulate trade-offs and design decisions clearly
• A collaborative, proactive mindset with strong problem-solving skills

Nice to Have
• Knowledge of MLOps practices and experience with Data Version Control (DVC) or similar tools
• Knowledge of data pipelines, including designing production-grade GPU inference pipelines for high-throughput workloads
• Exposure to frontend or full-stack development
• Experience working in a startup or fast-paced product environment
• Experience building data pipelines or working with large-scale data processing

Why Join
• Build the computer vision and machine learning systems behind a product used by millions
• Fully remote with real autonomy and direct collaboration with the AI Research team
• A profitable, growing company with a global team

Compensation and Logistics
• Remote, full-time, open to applicants worldwide
• Compensation competitive, based on experience

We are seeking an AI Engineer to join our software, system and test engineering group.

You will assist in designing and developing agentic and multi-agent systems at scale using the LangChain and LangGraph frameworks, with a focus on scalable, production-grade applications. Join us to build your skills in Python, AWS and data science while contributing to advanced AI solutions for our clients.

This position is open to candidates based in Ukraine.

Support the design of agentic AI systems and multi-agent systems at scale

• Assist in developing production-grade AI applications with LangChain and LangGraph frameworks
• Contribute to implementing retrieval-augmented generation (RAG) evaluation methods
• Build and maintain vector databases for AI data storage and retrieval
• Apply data science techniques to improve AI system performance
• Collaborate with cross-functional teams to integrate AI solutions
• Develop scalable and efficient AI system architectures
• Troubleshoot and resolve system issues and bottlenecks
• Acquire knowledge about AI and machine learning advancements
• Document system designs and development processes
• Participate in code reviews and follow best practices
• Optimize cloud infrastructure with AWS services
• Deploy and monitor AI applications

Skils:

• Interest in designing and developing agentic AI systems and multi-agent systems
• Programming skills in Python with 2+ years of experience
• Familiarity with LangChain and graph frameworks such as LangGraph
• Understanding of the Amazon Web Services (AWS) cloud platform
• Background in data science or data engineering methodologies
• Knowledge of algorithms, data structures and machine learning techniques
• Familiarity with RAG evaluation and vector databases
• Willingness to contribute to scalable and production-grade AI solutions
• Problem-solving and analytical skills
• Experience or coursework in software, system or test engineering environments
• Collaboration and communication skills
• B2+ level English proficiency

With us you can:

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Relocation opportunities may be available for eligible candidates, depending on the role and openings at other EPAM locations
• Participate in volunteer, charity programs and communities (both technical and interest-based)
   

We focus on your professional growth:

• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
   

What we offer:

• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children

Kindly be advised that the set of benefits, including learning, certification, and other opportunities, may vary depending on the role you apply for. Our recruiter will be able to share more details about the specific opportunity during your general interview.

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of an AI product company in advanced manufacturing.
• Be part of a research focused team.

Responsibilities: 

• Research, test and develop generative AI based solutions.
• Collaborate with mechanical engineers to enhance your research.
• Design and implement end-to-end AI solutions that integrate with existing systems.
• Collaborate with software engineers and product teams to understand business needs and translate them into technical solutions. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• University degree in Computer Science, Engineering, Mathematics, or a related field. 
• Proven experience in developing generative AI or machine learning models.
• Commercial experience in using large language models.
• Programming skills in languages such as Python or JavaScript.
• Familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies

Client Overview

Our Client is a publicly listed, global leader in creative effectiveness and marketing decision-making, headquartered in the UK. For over two decades, the company has helped the world's leading advertisers predict and improve the commercial impact of their advertising using a proprietary methodology rooted in behavioral science — measuring audiences' instinctive emotional responses to creative content rather than relying on rational, questionnaire-driven analysis. Its effectiveness metrics, predicting both long-term brand growth and short-term sales impact, are independently validated and backed by one of the industry's largest databases of professionally tested ads.

Project Description

The Client is transforming its human-panel ad testing methodology into an AI-powered prediction platform trained on 140K+ professionally surveyed ads already predicts human emotional responses to video ads. The roadmap includes brand recognition social ad scoring models, migration from Azure to AWS SageMaker, and an API-first SaaS platform, with a 6-12 month time to market. 

Requirements

• 5+ years of hands-on ML engineering experience, including training and fine-tuning deep learning models end to end (beyond consuming pre-trained APIs or LLMs)
• Strong PyTorch expertise
• Practical experience with multimodal architectures — video, audio, and fusion/ensemble models (e.g., VideoMAE, ViT, BEATs, HuBERT, CLIP-class encoders)
• Solid computer vision background and experience with video data pipelines (frame sampling, feature extraction and pre-caching, large-scale video datasets)
• Proven transfer learning and fine-tuning experience: selective layer unfreezing, handling class imbalance and label scarcity
• MLOps skills: experiment tracking (Weights & Biases or similar), reproducible training pipelines, dataset versioning and management, cloud GPU training (AWS SageMaker, Lightning AI, or Azure ML)
• Strong software engineering fundamentals: Git workflows, CI/CD, automated testing, code review culture
• Cost-aware experimentation mindset — able to evaluate ideas quickly, prioritize high-value directions, and stop dead-end experiments early
• Individual contributor profile with a proven ability to mentor and upskill colleagues by example
• Pragmatic, delivery-focused attitude and a genuine growth mindset

• Excellent English communication skills; comfortable working directly with UK-based senior leadership

   

Nice to Have

• Affective computing / emotion recognition from video or audio
• Audio ML: speech understanding, music and audio classification
• Saliency prediction and visual attention modeling
• OCR and on-screen text understanding
• Using LLMs for automated feature extraction or labeling within ML pipelines
• Background in AdTech, MarTech, media/creative analytics, or behavioral science
• Experience migrating ML workloads between cloud providers (Azure → AWS)

• Familiarity with AI-assisted development workflows (Claude Code, Copilot, Cursor)

   

Responsibilities

• Take ownership of the existing multimodal emotion prediction model: master its architecture and limitations, and drive accuracy improvements, particularly on underrepresented emotion classes
• Design, train, and evaluate new models on the roadmap: brand fluency/recognition, emotional intensity, saliency, and social ad performance prediction
• Bring experience-based judgment to model strategy: assess ideas quickly, select the highest-value experiments, and protect the team from costly dead ends in training time and GPU spend
• Build and improve ML infrastructure: migrate training workloads to AWS SageMaker (or Lightning AI), establish proper dataset management, and move from aggregated data snapshots to respondent-level training data via direct database integration
• Extend the models with new capabilities: speech understanding encoders, OCR, and LLM-based metadata feature extraction
• Write production-quality, tested code within a modern CI/CD and AI-assisted development workflow
• Actively share knowledge: pair with and coach internal engineers transitioning into ML, raising the team's overall competency so expertise is retained in-house
• Work directly with the Client's technology leadership on roadmap prioritization, evaluation frameworks, and platform architecture
• Contribute to shaping an API-first SaaS platform built on top of the models

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Job Summary

We are seeking a highly organized and detail-oriented professional to support project planning, execution, and control. This role combines the functions of a coordinator and junior project manager and requires strong communication skills, multitasking, and a proactive approach to problem solving.
The primary objective of this position is to ensure the smooth running of projects by coordinating teams, monitoring deadlines, maintaining documentation, and supporting communication with clients and stakeholders.

Key Responsibilities:
- Assist in planning and tracking project progress to ensure adherence to deadlines and key milestones.

- Communicating complex information in a clear and understandable manner.

- Communicating and collaborating with internal and external teams to ensure completion of tasks and alignment with project objectives.

- Monitoring data quality and promptly escalating risks or issues that may impact scope, timelines, or quality.

- Providing regular project updates to clients and stakeholders, aligning expectations, and ensuring transparency.

- Maintaining and updating key project documentation: budget reports, trackers, meeting minutes, delivery schedules.

- Monitoring production KPIs (speed, quality), conducting random quality checks to maintain consistent results.

- Identifying and escalating scope changes at client request to the appropriate internal teams.

- Organizing and conducting meetings with the team/clients to agree on goals, discuss issues, and discuss project status.

- Assisting in resolving project issues and optimizing work processes to improve efficiency.

Requirements:

- Higher education in business, IT, or a related field (preferred)
- Experience in project coordination, operations, or support
- Understanding of the project lifecycle and basic Project Management principles
- Excellent planning, organization, and multitasking skills
- Strong communication skills, ability to clearly communicate information
- Ability to handle risks and problems, results-oriented
- Experience with project management tools (JIRA, Trello, Asana)
- Skills in working with spreadsheets, reports, and calculations
- Mandatory language requirements

Fluency in English and Russian/Ukrainian (oral and written)
will be an advantage

• Experience in data annotation or markup;
• Understanding of Agile/Scrum, Kanban;
• Experience working with cross-functional teams;
• Basic knowledge of IT processes and software development.
   

About us

We're building an AI boxing coach. A fighter films a round on their phone, we tell them what's wrong with their technique, and then we build them a training plan to fix it: specific drills targeting their specific faults. The kind of coaching you'd get from a good trainer, for people who mostly train alone.

We're a remote team of 4. Early stage, shipping fast, no process overhead.

Where we are

• A working punch classifier running on pose data
• 15 form rules live in production: feet apart, hip rotation, full arm extension, guard drop, elbow flare, and others

• An in-house labeling team producing our training data

   

What you'd work on

• Adding form rules. Some are geometry and heuristics on skeleton data, some need small models trained on our labeled clips. Knowing which is which is part of the job.
• Teaching the model defensive movement: slips, rolls, blocks. The current classifier is built around punches thrown from two hands, so head movement probably needs a different approach. Working out what that approach is would be yours.
• Improving the punch classifier over time: more classes, better accuracy.

• Owning the labeling spec. You decide what the labelers annotate and make sure what comes back is usable.

   

You

• 2+ years computer vision. Pose estimation or action recognition strongly preferred.
• Comfortable with temporal models over sequence data, not only static image work.
• For at least the first couple of months you'll be the main developer, as I'll be focused on product and partnerships. We'll talk regularly and I'll set the priorities, but how things get built is yours. Nobody is going to review your approach for you, and there's no existing playbook to follow.
• We work over video, camera on. Hours are flexible, but you're reachable and you show up to calls.

What we offer

• Real ownership of the CV work. You decide how things get built, not just implement someone else's spec.
• Competitive salary, paid monthly in USD
• Fully remote
• Flexible hours. We care about what ships, not when you're online.

How we hire

Three steps, and we move fast:

1. Application. Tell us two things. First, relevant experience: action or gesture recognition, pose or skeleton data, video pipelines. What you built, and what the numbers were. Second, why this job specifically.
2. Call. 20 minutes, video. We go through one of your projects properly and you ask us whatever you want.
3. Paid test task. Real data from our dataset, scoped to around 4 hours, flat fee paid on submission whether or not we move forward.

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

ORIL is seeking a highly skilled Senior AI/ML Engineer to architect and scale our mission-critical, AI-driven data platform. At the core of our engineering culture is a steadfast commitment to performance, reliability, and uncompromising data integrity. The ideal candidate is an autonomous problem-solver who thrives in an agile environment, takes end-to-end ownership of complex systems, and pairs a bias for action with a dedication to robust, stable deployments.

 

Project:

Our client is a US-based innovator providing a centralized data platform for multi-family real estate. The product uses BI and AI analytics to help operators optimize marketing spend and operational efficiency. A core AI feature of this platform is an intelligent chatbot designed to help users seamlessly manage workflows, query data, and surface actionable insights.

What are we looking for?

• 5+ years of experience building and owning production-grade backend and ML systems in Python;
• Proven experience designing and deploying complex, multi-step LLM workflows and conversational agents (chatbots) using frameworks like LangChain or LangGraph;
• Deep understanding of RAG (Retrieval-Augmented Generation) pipelines: from chunking and embedding strategies to retrieval optimization and prompt engineering;
• Experience with "Text-to-SQL" or translating natural language into complex data queries, as the chatbot will interact heavily with BI analytics;
• Experience with LLM observability, tracing, and evaluation frameworks (e.g., Langfuse, Braintrust, Arize Phoenix, Ragas, or DeepEval);
• Experience with systematic prompt lifecycle management, versioning, and algorithmic optimization (e.g., DSPy);
• Experience profiling and minimizing time-to-first-token (TTFT) and overall response latency for real-time conversational agents;
• Strong analytical skills with the ability to explore datasets, identify patterns, measure outcomes, and derive actionable insights; 
• Familiar with data cleaning and normalization techniques to ensure accurate, consistent, and reliable data for analysis and AI-driven applications;
• Curious about how multi-family real estate works and motivated to understand the key metrics behind the business (marketing spend, operational efficiency etc.) to better tune AI outputs;
• English level: Upper-Intermediate (B2+).

What will you do?

• Design, develop, and own the core AI architecture powering the platform's intelligent chatbot and automated BI insights;
• Build and refine advanced RAG pipelines to ensure the chatbot surfaces accurate;
• Develop robust AI agents capable of managing platform processes and executing complex operational tasks on behalf of the user;
• Set up and maintain automated CI/CD gates that run LLM evals and integration tests;
• Maintain a high shipping tempo, continuously iterating on chatbot features based on user feedback and internal telemetry;
• Diagnose and fix complex issues in the AI pipeline using advanced tracing and observability tools;
• Work closely with data engineers and product managers to refine the technical roadmap and ensure the AI seamlessly integrates with the broader BI platform.

We Offer:

Working conditions:

• Ability to grow with an ambitious niche-focused company
• Competitive compensation;
• Accounting Support Services;
• Flexibility to work from anywhere (fully remotely or in our office in Lviv);
• Comprehensive day-off policy, including public holidays and special events
• Education & certification budget + corporate education events and trainings
• Wellness budget
• The environment and culture that promotes personal and team development.

Application Process:

• Initial Screening: Call with Recruiter.
• Technical Interview.
• Client Interview.
   

Ready to build the future of AI-driven real estate operations? Apply now and let’s get to work!

Ми шукаємо AI Engineer, який підсилить нашу команду розробки штучного інтелекту. Це роль не про "просте підключення APІ чи поверхеневий інжиніринг запитів", а про глибоку інженерну й системну рооту на інтеграцію LLM, розробкою аріхектурних даних.
Якщо ти зацікавлений у даній позиції, читай нижче опис по вимогам/задачам, та якщо ти відповідаєш вимогам, залишай резюме!

Вимоги до досвіду:

• досвід комерційної розробки: не менше 3 років;
  Інструменти та технології: Python, REST API, OpenAPI/Swagger, JSON, Docker, PostgreSQL/MongoDB, Redis, CI/CD;
   
• впевнене володіння Python як основною мовою розробки;
  Необхідна екосистема Python: Python 3.10+, FastAPI, Flask (як плюс), Pydantic, Pydantic AI, asyncio, aiohttp/httpx, requests, SQLAlchemy, Alembic, Celery/RQ, pytest, unittest, mypy, ruff, black, isort, pre-commit, logging, structlog, pathlib, typing, dataclasses;
   
• досвід розробки backend-сервісів, API та інтеграцій;
  Інструменти та технології: FastAPI, REST API, WebSockets, SSE, OpenAPI/Swagger, Postman, JSON Schema, PostgreSQL, Redis, SQLAlchemy, Docker, docker-compose, GitHub Actions/GitLab CI;
   
• обов'язкове вміння самостійно писати чистий, підтримуваний та архітектурно коректний код без використання додаткових ШІ-інструментів (AI tools);
  Необхідні знання: OOP (ООП), SOLID, DRY, KISS, YAGNI, dependency injection, clean architecture, layered architecture, design patterns, error handling, logging, unit/integration testing, code review;
   
• досвід роботи з Docker та базовою інфраструктурою розгортання;
  Інструменти та технології: Docker, Docker Compose, Dockerfile, volumes, networks, multi-stage builds, environment variables, secrets, logs;
   
• досвід розробки ШІ-продуктів (AI products) на базі пропрієтарних моделей;
  Інструменти та технології: OpenAI API, Anthropic Claude API, Google Gemini API, OpenRouter, LiteLLM;
   
• досвід розробки ШІ-продуктів на базі local-hosted моделей;
  Інструменти та технології: vLLM, Ollama, llama.cpp, Text Generation Inference, Hugging Face Transformers, Hugging Face Hub, sentence-transformers, PyTorch, tokenizers, GGUF, AWQ, GPTQ, quantization, batching, streaming inference;
   

• досвід роботи з vLLM / llama-серверами та налаштуванням параметрів інференсу;
  Необхідні знання: context window, max tokens, temperature, top_p, top_k, repetition penalty, stop sequences, seed, batch size, concurrency, latency, throughput, tokens/sec, GPU memory, KV cache, cost per request;

  Інструменти: vLLM, Ollama, llama.cpp, TGI, Prometheus/Grafana (як плюс);
   

• досвід підбору моделей під робочі завдання;
  Необхідні знання: порівняння моделей за якістю, вартістю, latency, context window, multilingual quality, tool calling, structured output, safety, hallucination rate;
  Інструменти: OpenRouter, LiteLLM, Hugging Face Leaderboards, LMSYS/Chatbot Arena (як орієнтир), Langfuse, LangSmith, PromptFoo, DeepEval, Ragas;
   
• досвід роботи з vector RAG;
  Інструменти та технології: LangChain, LangGraph, LlamaIndex, Haystack, Qdrant, Weaviate, Pinecone, Chroma, FAISS, pgvector, Elasticsearch/OpenSearch, BM25, hybrid search, re-ranking;
  Необхідні знання: chunking strategy, embeddings, metadata filtering, query rewriting, retrieval evaluation, rerankers, grounding, citations, hallucination control;
   
• досвід роботи з graph RAG / knowledge graph RAG;
  Інструменти та технології: Neo4j, NetworkX, GraphRAG, LangChain Graph QA, LlamaIndex Knowledge Graph, RDF/SPARQL (як плюс);
  Необхідні знання: entity extraction, relationship extraction, graph traversal, semantic links, hybrid retrieval, context assembly;
   
• досвід побудови агентних систем;
  Інструменти та технології: LangGraph, LangChain Agents, LlamaIndex Agents, CrewAI, AutoGen, Semantic Kernel, Pydantic AI, OpenAI function calling / tool calling, Anthropic tool use, MCP;
  Необхідні знання: ReAct, planner-executor, supervisor pattern, multi-agent orchestration, memory, tool routing, state management, fallback logic, human-in-the-loop, guardrails;
   
• досвід роботи з AI workflow engine, обов'язково n8n;
  Інструменти та технології: n8n, webhook nodes, HTTP Request node, AI Agent node, credentials, triggers, queues, error workflows, custom nodes, workflow versioning;
   
• досвід побудови evaluation та observability для LLM-продуктів;
  Інструменти та технології: Langfuse, LangSmith, PromptFoo, Ragas, DeepEval, TruLens, Arize Phoenix, Weights & Biases Weave, Helicone, OpenTelemetry;
  Метрики: accuracy, groundedness, relevance, faithfulness, hallucination rate, refusal rate, latency, cost per request, token usage, context utilization, regression rate;
   
• розуміння інформаційної безпеки при роботі з ШІ;
  Необхідні знання: PII, sensitive data, prompt injection, data leakage, secrets management, RBAC, audit logs, sandboxing tools, vendor data policies;
   
• англійська мова: Не нижче Upper-Intermediate. Необхідна для читання документації, роботи з API, аналізу моделей, технічного листування та підготовки design docs.
   

Буде плюсом:

• знання Node.js;
• глибокі знання context engineering;
• глибокі знання NLP;
• досвід fine-tuning моделей.

Основні задачі:

• розробляти production-ready ШІ-сервіси, backend-компоненти, API та інтеграції для внутрішніх і зовнішніх ШІ-продуктів компанії;
• писати чистий, підтримуваний, тестований та архітурно коректний код на Python;
• проєктувати та реалізовувати сервіси на Python/FastAPI для роботи з LLM, RAG, агентними системами та workflow-автоматизацією;
• інтегрувати пропрієтарні моделі через API: OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, Mistral, OpenRouter та інші затверджені компанією сервіси;
• піднімати, налаштовувати та підтримувати local-hosted моделі через vLLM, Ollama, llama.cpp, TGI або аналогічні інструменти;
• підбирати моделі під конкретні бізнес-завдання з урахуванням якості, швидкості, вартості, latency, context window, доступності, безпеки та стабільності результату;
• налаштовувати параметри інференсу моделей: temperature, top_p, max tokens, context window, batching, streaming, concurrency, rate limits, retry logic;
• реалізовувати vector RAG-пайплайни: завантаження даних, очищення, chunking, embeddings, індексація, retrieval, reranking, генерація відповіді, оцінка якості;
• реалізовувати graph RAG / knowledge graph RAG-підходи для завдань, де потрібна робота зі зв'язками між сутностями, документами, користувачами, договорами, клієнтами або бізнес-процесами;
• работувати з векторними базами даних: Qdrant, Weaviate, Pinecone, Chroma, FAISS, pgvector;
• работувати з графовими базами та інструментами: Neo4j, NetworkX, GraphRAG-підходи;
• будувати агентні системи: single-agent, multi-agent, planner-executor, supervisor, tool-using agents, human-in-the-loop flows;
• реалізовувати tool/function calling, structured outputs, JSON schema validation, retry/fallback logic та безпечну обробку відповідей моделей;
• інтегрувати агентні системи з корпоративними інструментами: CRM, бази знань, документи, пошта, календар, Slack/Teams, Jira, Confluence, Google Drive, Microsoft 365, внутрішні API;
• проєктувати та впроваджувати AI workflow automation на базі n8n: webhooks, triggers, AI Agent nodes, HTTP nodes, credentials, error workflows, черги, інтеграції з зовнішніми системами;
• розробляти eval/regression-фреймворки для перевірки якості LLM-відповідей, промптів, RAG та агентних сценаріїв;
  налаштовувати observability та моніторинг ШІ-систем: Langfuse, LangSmith, PromptFoo, Ragas, DeepEval, Arize Phoenix, Helicone, OpenTelemetry;
• контролювати ключові метрики: latency, cost per request, token usage, groundedness, hallucination rate, relevance, accuracy, refusal rate, error rate, regression rate;
  проводити технічні експерименти з моделями, промптами, RAG-підходами, агентними патернами та параметрами інференсу;
• брати участь у завданнях з fine-tuning / model adaptation за наявності потреби: підготовка датасетів, навчання, валідація, порівняння результатів з baseline;
• спільно з Prompt Spec Engineer впроваджувати prompt/spec architecture в код, забезпечувати версіонування промптів, трасування, тестування та контроль якості;
• спільно з Product Manager переводити продуктові вимоги в технічну архітектуру, API-контракти, схеми даних та план реалізації;
• забезпечувати безпеку ШІ-сервісів: захист від prompt injection, контроль доступу, фільтрація чутливих даних, логування, аудит, безпечне зберігання секретів;
• підтримувати сервіси в production: аналізувати інциденти, виправляти помилки, оптимізувати продуктивність, знижувати вартість запитів, покращувати стабільність.

Що компанія пропонує:

• працюємо в сучасному та стильному офіс в ближньому центрі;
• безкоштовний корпоративний трансфер (дім-офіс-дім);
• забезпечуємо якісним та смачним кейтерингом прямо в офісі;
• корпоративні заняття йогою та медитацією + корпоративні знижки на здорове харчування;
• WELCOME bonus - фінансовий бонус від компанії на початку співпраці;
• релокейт пакет (оплата квитків у Львів + перший та останній місяць + рієлторські послуги).

Cargofy is building the AI-native operating system for global freight. Cargofy deploys autonomous AI agents that automate procurement, dispatching, negotiations, tracking, and operations for carriers, shippers, and 3PLs across the US, Europe, and Asia. Our platform processes 100,000+ loads per day and hundreds of thousands of real-time events — replacing manual logistics with fully autonomous AI.

We need an AI Creator to put product video on a production line and make Cargofy as recognizable on screen as it is in the market.

Why This Role Exists Now

Logistics operators deciding whether to trust an autonomous agent with their dispatching don't want to read about it. They want to see it run. We ship fast — agents go to production in weeks. The old video model can't keep pace. So we're doing it the way a company that sells digital workers should: with AI. Your job is to turn that into an engine.

What Winning Looks Like

• Product video ships on the same clock as the roadmap, not weeks behind it
• Every launch has a clip; sales has assets that close instead of explain
• Cargofy has a recognizable visual language across every channel — not a folder of one-offs
• A library of reusable templates and workflows so production scales without starting from zero

What You Will Own

• Product videos — 30–60 second clips showing what Cargofy actually does, script to finished clip, end to end
• Channel distribution — cut one source into ready versions for LinkedIn, YouTube, events, and ads
• Content coverage — feature releases, product launches, case studies, sales and onboarding assets
• Production system — templates and workflows that scale output without scaling headcount
• Visual language — iterate on tone, visuals, and pacing until the look is unmistakably Cargofy

Who You Are

• Already making strong short-form video with AI tools — Runway, Kling, Veo, HeyGen, Pika, ElevenLabs, or similar
• Show the work rather than describe it
• Understand B2B product marketing — what a clip is for, not just how it looks
• Deliver finished videos, not source files for someone else to finish
• Experience with AI video for SaaS or tech products is a plus

Why Cargofy

• A clear mandate to build with AI, not against a headcount cap
• Fast cycles — script to brief to clip in days, not weeks
• Direct line to the team and the product, with real ownership of the output
• Contract, part-time / project-based to start — full-time on the table if it's a match
• Remote-first with offices in Kyiv, Warsaw, and Houston

🚀 We are looking for a Middle AI Engineer to build scalable AI-powered applications, developer tools, and workflow automation solutions that improve engineering productivity and deliver measurable business value.

This role is ideal for a strong Python engineer with hands-on experience building and deploying LLM-based applications. You will work on solutions involving RAG, AI agents, model integrations, backend services, and AI evaluation.

🎯 Responsibilities

- Design, build, and deploy LLM-powered applications from prototype to production.

- Develop AI agents, tool-using workflows, and multi-step automation solutions.

- Build and improve RAG pipelines using internal and third-party data sources.

- Integrate commercial and open-weight models such as OpenAI, Anthropic Claude, Google Gemini, and Llama-based models.

- Develop AI-powered capabilities such as code assistance, document generation, summarisation, knowledge search, and workflow automation.

- Build backend services, APIs, integrations, and data flows using Python.

- Implement embeddings, vector search, reranking, structured outputs, and tool calling.

- Evaluate AI outputs and improve relevance, accuracy, reliability, latency, and cost efficiency.

- Add logging, monitoring, error handling, fallback mechanisms, and output validation to AI systems.

- Deploy and maintain AI services in cloud environments.

- Collaborate with product, engineering, and business teams to deliver production-ready AI solutions.

🧩 Requirements

- 3+ years of commercial Python development experience.

- Hands-on experience building and deploying LLM-powered applications.

- Practical experience with at least one of the following:

  - RAG systems;

  - AI agents;

  - multi-step LLM workflows.

- Experience developing backend systems, REST APIs, integrations, and data flows.

- Experience with FastAPI, Django, Flask, or another Python backend framework.

- Hands-on experience with LangChain, LangGraph, LlamaIndex, or a similar AI orchestration framework.

- Experience working with OpenAI, Anthropic, Gemini, Llama-based models, or similar technologies.

- Practical understanding of prompt design, structured outputs, tool calling, and output validation.

- Experience with embeddings, vector search, and at least one vector database.

- Understanding of RAG concepts such as chunking, retrieval, reranking, and response generation.

- Experience evaluating and improving LLM output quality.

- Experience with Docker, Git, automated testing, and CI/CD workflows.

- Experience deploying applications to AWS, Azure, GCP, or another cloud platform.

- Understanding of common production AI challenges, including hallucinations, latency, rate limits, reliability, and cost control.

- English level: Upper-Intermediate or higher.
 

🧩 Nice to Have

- Experience with multi-agent systems.

- Experience building custom tools for AI agents.

- Familiarity with MCP servers, clients, or MCP-based integrations.

- Experience with LLM evaluation and observability tools such as LangSmith, Langfuse, Arize Phoenix, or similar.

- Experience with advanced retrieval techniques, hybrid search, or retrieval evaluation.

- Experience working with open-weight models and model-serving solutions.

- Familiarity with AI safety, guardrails, prompt injection protection, and responsible AI practices.

- Experience with Kubernetes or scalable AI service deployment.

- Experience building AI-powered developer tools.

🧩You'll have an opportunity to:

Build production-ready AI applications used by real users.

Work with modern LLM technologies, AI agents, and RAG systems.

Collaborate with experienced international engineering teams.

Gain hands-on experience with rapidly evolving AI frameworks and cloud platforms.

Solve challenging engineering problems and contribute to scalable AI solutions.

Continuously grow your expertise in Generative AI and modern software engineering

About us:

EveryMatrix is a leading B2B SaaS provider delivering iGaming software, content and services. We provide casino, sports betting, platform and payments, and affiliate management to 200 customers worldwide.

But that's not all! We're not just about numbers, we're about people. With a team of over 1000 passionate individuals spread across twelve countries in Europe, Asia, and the US, we're all united by our love for innovation and teamwork.

EveryMatrix is a member of the World Lottery Association (WLA) and European Lotteries Association. In September 2023 it became the first iGaming supplier to receive WLA Safer Gambling Certification. EveryMatrix is proud of its commitment to safer gambling and player protection whilst producing market leading gaming solutions.

Join us on this exciting journey as we continue to redefine the iGaming landscape, one groundbreaking solution at a time.

We are looking for a passionate and dedicated AI Engineer to join our team in Lviv!

About the job:

We’re looking for an AI/ML Engineer to support and build AI-powered solutions that enhance automation, analytics, and intelligent workflows across our products. You’ll work with modern LLMs, AI agents, retrieval systems, and scalable backend services, taking ideas from prototype to production in a fast-moving environment and building scalable solutions in a high-impact domain. The ideal candidate for us has strong software engineering fundamentals, practical experience with generative AI systems, and hands-on experience building robust pipelines and production-grade solutions.

What You'll get to do:

• Design, develop, and deploy AI-powered applications and services.
• Integrate LLMs and AI APIs into production systems.
• Build and optimize RAG pipelines, embeddings workflows, and vector search solutions.
• Develop AI agents and workflow automation systems.
• Work with structured and unstructured data for AI-driven use cases.
• Collaborate with Data Engineers and Backend Engineers on scalable infrastructure.
• Monitor AI system performance, quality, latency, and cost efficiency.
• Experiment with prompt engineering, fine-tuning, and model evaluation techniques.
• Participate in architecture discussions and contribute to technical decision-making.

What You need to know:

• Degree in Computer Science, Mathematics, Engineering, or equivalent field.
• 3+ years of hands-on experience in applied AI-engineering.
• Strong programming skills in Python.
• Experience working with LLMs and modern AI frameworks such as LangChain, LlamaIndex, or similar.
• Understanding of RAG architectures, embeddings, vector databases, and semantic search.
• Experience integrating external APIs and cloud-based AI services.
• Knowledge of REST APIs, microservices, and scalable backend architectures.
• Familiarity with Docker, CI/CD, and cloud platforms, especially GCP.
• Strong problem-solving skills and ability to work independently.
• Interest in AI automation, intelligent systems, and applied generative AI solutions.
• Experience in Python backend engineering will be a plus.
   

Here's what we offer:

• Start with 22 days of annual leave, with 2 additional days added each year, up to 32 days by your fifth year with us.
• 3 sick leave days per year, no doctor's note required; 30 medical leave days with medical allowance
• Hybrid work schedule is available after the first three months of employment with 80/20 office/home format until the end of 2026. Starting from 2027, the policy will transition to primarily office-based work, with up to 10 work-from-home days per year with manager approval.
• Benefit from two Free Fridays each year, limited to one per quarter.
• Daily catered lunch or monthly lunch allowance. 
• Private Medical Subscription. 
• Access online learning platforms like Udemy for Business, LinkedIn Learning or O’Reilly, and a budget for external training.
• Gym allowance.
• Corporate English lessons.
• Support for New Parents:
• 21 weeks of paid maternity leave, with the flexibility to work from home full-time until your child turns 1 year old.
• 4 weeks of paternity leave, plus the flexibility to work from home full-time until your child is 13 weeks old.

Our office perks include on-site massages and frequent team-building activities in various locations.

At EveryMatrix, we're committed to creating a supportive and inclusive workplace where you can thrive both personally and professionally. Come join us and experience the difference!

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