Jobs Ukraine, ML / AI

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. 

We are looking for a Middle AI Engineer who will help us build, integrate, and scale AI-powered products that solve real business challenges.

This role is focused on creating production-ready AI solutions — from backend services and LLM integrations to RAG systems, AI agents, and workflow automation. You will work closely with Product Managers, developers, and business teams to transform ideas into reliable AI products that deliver measurable value.

What you will do:

• Develop production-ready AI services, backend components, APIs, and integrations for internal and external AI products.
• Design and implement AI solutions based on Large Language Models (LLMs), RAG architectures, AI agents, and workflow automation.
• Build and optimize Python-based services and backend infrastructure with a focus on scalability, reliability, and maintainability.
• Integrate and work with different types of AI models — including proprietary APIs (OpenAI, Anthropic, Gemini, etc.) and locally hosted models.
• Design and improve RAG pipelines: data processing, embeddings, vector search, retrieval optimization, knowledge bases, and AI response quality improvement.
• Develop AI agent systems and automation workflows, including integrations with external APIs, corporate systems, and internal tools.
• Conduct technical experiments with models, prompts, architectures, and inference parameters to identify the most effective solutions.
• Implement AI quality evaluation and monitoring approaches: analyze model performance, improve reliability, reduce errors, and optimize system efficiency.
• Collaborate with Product Managers and cross-functional teams to translate product requirements into technical solutions and scalable architectures.

• Ensure AI services are secure, stable, and production-ready by monitoring performance, resolving issues, and continuously improving systems.

   

What we expect from you

• 3+ years of commercial software development experience with strong Python expertise.
• Experience building backend services, APIs, and integrations using modern technologies.
• Strong understanding of software engineering principles: clean code, architecture patterns, testing, scalability, and maintainable solutions.
• Practical experience developing AI products based on Large Language Models (LLMs).
• Hands-on experience with RAG systems, embeddings, vector databases, retrieval optimization, and AI application development.
• Experience working with AI model integrations, including external APIs and/or locally deployed models.
• Understanding of AI agents, workflow automation, and approaches to building reliable AI systems.
• Experience with Docker, CI/CD, and production deployment processes.
• Ability to analyze AI system performance and improve quality, efficiency, and reliability.
• Upper-Intermediate English level (B2+) 

Will be a plus:

• Experience with fine-tuning or adapting AI models.
• Experience with MLOps / LLMOps practices.
• Knowledge of NLP approaches.
• Experience with cloud platforms and scalable infrastructure.

What we offer

• Competitive compensation up to $4,000, depending on your experience and expertise.
• Office-based work in Lviv with the possibility of a hybrid schedule.
• High level of technical ownership and the opportunity to solve challenging engineering problems.
• Professional development opportunities: company-sponsored courses, training, and access to necessary tools and resources.
• A team of experienced specialists who value expertise, initiative, and high-quality engineering.
• The opportunity to become one of the key engineers shaping the company’s AI direction.
• Relocation support for candidates from other cities, including assistance with moving and adaptation in Lviv.

About us

DroneOps is a company creating innovative UAV-related products, focused on UAV autonomy and navigation, founded in 2023. We are a team of innovators and inventors who take on the duty to help the armed forces of Ukraine defend our country and democracy by providing reliable advanced systems that simplify their work, improve personnel safety, and enable more cost-effective and precise UAV mission execution.

Overview

We are looking for a Middle / Senior Computer Vision / Deep Learning Engineer to extend our onboard navigation capabilities with modern perception and learning-based methods.

This is a hands-on R&D role: you work from research and prototypes to production on edge hardware, collaborate with software, and flight teams, and help shape how new CV/DL features are built and shipped. The role suits someone who can follow state-of-the-art work, implement what fits our constraints, and care about real-world performance—not only offline benchmarks.

Responsibilities

Relocalization & navigation

• Design and develop satellite, map, and semantic navigation capabilities that improve the overall quality of our navigation
• Build and maintain pipelines for map and reference-data preparation before missions
• Extend the existing visual-inertial navigation stack with relocalization and map-based aiding features
• Develop training pipelines for these tasks (data preparation, training, evaluation, and iteration)
• Create utilities that make map preloading and mission setup convenient for operators and integrators
•  

Research & implementation

• Track relevant research and industry approaches; prototype and adopt methods where they clearly improve the product
• Reimplement or adapt algorithms when off-the-shelf solutions do not fit our data, hardware, or latency requirements
• Define evaluation metrics and acceptance criteria for new features before field and deployment rollouts
•  

Edge deployment & production

• Optimize models and inference for target onboard hardware
• Integrate new features into the production codebase with stable APIs, logging, and failure handling
• Take part in architecture decisions, code review, and team practices that keep production quality high as the stack grows
•  

Required skills & experience

• 3+ years of practical experience in computer vision and deep learning
• Strong Python; ability to write clear, maintainable code for experiments and production paths
• Experience with training and deploying deep learning models (PyTorch)
• Familiarity with model optimization for edge or embedded devices (pruning, quantization, ONNX/TensorRT-class tooling, or equivalent)
• Comfort working with geospatial or map-related data and preprocessing pipelines
• Practical production mindset: reproducible experiments, versioning, and validation on real data
• English B2+ for documentation and technical discussion; Ukrainian for day-to-day team communication
•  

Nice to have

• Experience with deep learning keypoint detection and matching approaches
• Comfortable with geometric computer vision (camera models, epipolar geometry, robust estimation)
• Multi-sensor fusion / SLAM / EKF background
• UAV, robotics, or aerospace field experience
• Experience with satellite or aerial imagery, semantic segmentation, or visual place recognition
•  

What we offer

• Competitive salary
• Reservation from mobilization
• Impact on improving our country's defense capabilities
• 21 days of vacation + public holidays, sick leaves

Softcery builds advanced AI systems for B2B SaaS companies. We partner with founders in the US and UK to design, build, and scale production-ready AI solutions that solve real business challenges. Our team focuses on complex AI engineering — systems that are technically robust, business-aligned, and built to scale. We combine deep technical expertise with strong product thinking, helping companies move from AI ambition to real, production impact.

We are looking for an AI Engineer to design and build AI agents, Voice AI solutions, and intelligent automations. You'll work with modern LLMs, agent frameworks, and production AI systems that solve real business problems.

What You'll Do:

• Build AI agents, Voice AI solutions, and intelligent automation workflows.
• Design and develop AI-powered applications using modern LLMs and agent frameworks.
• Build RAG pipelines and integrate AI systems with APIs, databases, CRMs, and third-party services.
• Design prompts, agent workflows, memory, and tool-calling capabilities.
• Optimize AI systems for performance, reliability, scalability, and cost efficiency.
• Explore new AI models, frameworks, and technologies, applying the best solutions to real-world use cases.
• Collaborate with engineers and clients to deliver production-ready AI solutions.

What We're Looking For:

• 2+ years of commercial experience in AI Engineering.
• Strong Python skills.
• Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and AI-powered applications.
• Experience with LangGraph, LangChain or similar frameworks.
• Understanding of prompt engineering, RAG, embeddings, vector databases, and AI orchestration concepts.
• Strong problem-solving skills, ownership mindset, and eagerness to learn.
• English – Upper-Intermediate (B2) or higher.

What We Offer:

• Structured onboarding – a clear onboarding plan, documented workflows, and a team that has your back.
• Flexible remote schedule – work from wherever and whenever you're most productive.
• Learning budget – we cover books, courses, English lessons, and AI tools for your professional growth.
• Full accounting support – so you can focus on the work, not the paperwork.
• Time off – 20 paid vacation days, 12 sick days, 2 paid period leave days/month (for women), and your birthday off.
• IT Cluster membership – access to professional events and networking opportunities in the local tech community.

🔁 Hiring Process: Initial Call → Qualification Interview → Test Task → Review Test Task.
 

If you're excited about building AI products that solve real business problems and want to work with the latest AI technologies every day, we'd love to meet you 👋

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:

• Bachelor’s or Master’s 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.

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).

Team Summary

Our distributed team is looking for an experienced Applied Scientist with a strong background in Large Language models to develop high-performance Generative AI features across Cloud and Edge environments.

Job Summary

In this role you will drive the transition from research to production by optimizing local inference through model compression and quantization for private, real-time Edge performance, while also engineering scalable RAG architectures and multi-agent systems for Cloud deployment. Your daily responsibilities encompass the full research lifecycle, including formulating hypotheses, generating synthetic datasets, fine-tuning LLMs, and validating safety and alignment, ultimately culminating in technical reports.

Responsibilities and Duties

— Design and implement advanced methods in prompt orchestration, fine-tuning (SFT/RLHF/DPO), and autonomous agentic workflows
— Curate high-quality training data from large-scale text and multi-modal sources
— Identify patterns in model hallucinations and visualize evaluation metrics for clear interpretation
— Tune hyperparameters and improve inference speed/accuracy through PEFT (LoRA/QLoRA) and advanced prompt engineering
— Collaborate with Product and Data Engineering teams to seamlessly integrate LLM features into the broader ecosystem
— Track and report progress using industry-standard benchmarks (MMLU, HumanEval, etc.) and custom internal KPIs
— Stay at the forefront of the field (e.g., State Space Models, new Transformer variants) and evaluate cutting-edge techniques for production readiness
— Engage in continuous technical growth and mentor junior colleagues to elevate the team's expertise

Qualifications and Skills

— 4+ years of commercial experience in Machine Learning, with a specific focus on the NLP or LLM domain
— Strong knowledge of Python3, NumPy, pandas, and modern text-processing libraries, PyTorch and Hugging Face (Transformers, PEFT, Accelerate)
— Proficiency in PEFT/LoRA and Reinforcement Learning techniques
— Deep understanding of attention mechanisms, tokenization, context window management, and embedding spaces 
— Practical experience in at least one of the following: Retrieval-Augmented Generation (RAG), — Fine-tuning, or Agentic frameworks
— Proven ability to manage and analyze massive datasets (>100GB) across text, image, and audio formats
— Hands-on experience crafting high-fidelity datasets and building robust data pipelines
— Expertise in prompt engineering, agentic framework design, and LLM pipeline orchestration
— Experience deploying LLMs to production environments using Triton Inference Server, vLLM, TGI, or ONNX
— Good written and spoken English

Nice to have

— Practical experience with Pinecone, Weaviate, Milvus, or Chroma 
— Advanced quantization (GGUF, AWQ, EXL2), pruning, and knowledge distillation
— Experience with LangChain, LlamaIndex, or AutoGen
— Basic understanding of web/client-server architecture and streaming API responses (Asyncio, aiohttp)
— Familiarity with RAGAS, DeepEval, or G-Eval
— Experience using Docker, Kubernetes, and cloud GPU orchestration (e.g., Run:ai, Lambda Labs)
— Knowledge of C++, Triton, or CUDA for custom kernel development

We offer multiple benefits that include

— The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member
— Competitive compensation and perks. Annual performance review
— Opportunity to receive a Performance Bonus for your individual achievements and a Loyalty Bonus recognizing your dedication to the company
— Gig-contract
— 21 paid vacation days per year, paid public holidays according to the Ukrainian legislation
— Development opportunities like corporate courses, knowledge hubs, and free English classes as well as educational leaves
— Medical insurance is provided from day one. Sick leaves and medical leaves are available
— Remote working mode is available within Ukraine only
— Free meals, fruits, and snacks when working in the office.

Team Summary

We are a distributed team that develops motion detection features for both Cloud and Edge environments, ensuring high performance and adaptability for diverse deployment needs. You can choose to focus on either Edge or Cloud solutions. Those interested in Edge will work on advanced computer vision algorithms and sensor-based detection methods to enable efficient real-time performance directly on devices. Those focusing on Cloud will develop scalable, high-performance motion detection solutions using cloud-based technologies, optimizing collaboration between Edge and Cloud for the best results.

You will be responsible for day-to-day research tasks, such as setting up hypotheses, gathering data for experiments, training and validating ML models, validating results, and writing a paper on your results.

Responsibilities and Duties

— Develop innovative machine learning algorithms. Implement advanced methods and technologies in model development

— Analyze large datasets to identify correlations and patterns. Visualize research results for clearer interpretation

— Tune hyperparameters and optimize algorithms. Improve models to enhance their performance and accuracy

— Provide consultations and collaborate with colleagues from other departments

— Report progress and project achievements to management

— Explore and evaluate new technologies in the field of machine learning. Implement cutting-edge ideas and techniques into production processes

— Engage in continuous self-improvement and technical skill development. Train and mentor junior colleagues to enhance the overall competence level within the team

Qualifications and Skills

— 4+ years in machine learning (computer vision domain)

— Practical experience in at least one of the following problems: classification, detection, segmentation

— Python3, NumPy, scikit-learn, pandas, SciPy

— Deep learning frameworks: PyTorch

— Experience in deploying machine learning models to production

— Good understanding of machine learning and deep learning concepts

— Good written and spoken English

Nice to have

— Practical experience with GANs, VAEs

— Probabilistic programming and bayesian framework

— Model optimization: pruning, quantization, knowledge distillation

— Basic understanding of web and client-server architecture

— asyncio, aiohttp, and other async libraries for back-end

— Basic understanding of Big Data, understanding of difference between MapReduce and in-memory processing

— Algorithms, data structures

— SQL, NoSQL

— Docker, Kubernetes, Kubeflow

— C++, Bash

We offer multiple benefits that include

— The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member

— Competitive compensation and perks

— Gig-contract

— 21 paid vacation days per year, paid public holidays according to the Ukrainian legislation

— Development opportunities like corporate courses, knowledge hubs, and free English classes as well as educational leaves

— Medical insurance is provided from day one. Sick leaves and medical leaves are available

— Remote working mode is available within Ukraine only

— Free meals, fruits, and snacks when working in the office.

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

About us:

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

Our mission:

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

Our goals:

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

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

What you’ll do:

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

It’s a match if you have:

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

Nice to have:

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

Preferred tech stack:

Core:

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

Nice to have:

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

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

About 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 Role

We're building AI-powered products and we need someone who can work across the full stack without needing a handoff at every layer. This role spans backend services, AI orchestration, real-time voice systems and frontend interfaces. You'll own features from design to deployment and be expected to debug issues that cut across all of them.

If your experience is limited to a single layer of the stack, or your AI exposure hasn't gone beyond side projects, this role isn't the right fit.

What You'll Do

• Design and build backend services and APIs using Node.js and Python
• Build and operate AI workflows using LangChain and LangGraph for orchestration, chaining and agent logic
• Use LangSmith for tracing, evaluation and debugging of AI pipelines in production
• Integrate real-time voice capabilities using LiveKit and related voice AI infrastructure
• Build frontend interfaces using React and Next.js that are fast, reliable and handle streaming AI responses cleanly
• Own features end to end from initial design through deployment, monitoring and iteration
• Handle async workflows, background jobs and real-world failure scenarios
• Set up logging, tracing and alerting so production issues surface before users report them
• Debug problems that span frontend, backend, AI pipelines and infrastructure simultaneously
• Work with product to turn vague requirements into well-scoped, shipped features
• Review code and maintain technical standards across the team

What You'll Need

• 5+ years of professional software engineering experience in production environments
• Strong hands-on experience with Node.js and Python at production scale
• Demonstrated experience building AI workflows using LangChain, LangGraph or comparable frameworks
• Working knowledge of LangSmith or equivalent tooling for AI observability and evaluation
• Experience building and operating backend APIs used by real users
• Solid experience with React and Next.js or equivalent frontend frameworks
• Strong understanding of async programming, streaming (SSE/WebSocket) and frontend state management
• Experience with MongoDB or similar document stores including data modelling trade-offs
• Comfort deploying and operating services on AWS, GCP or equivalent cloud environments
• Ability to debug across frontend, backend and AI layers using logs, traces and metrics

Good to Have

• Hands-on experience with LiveKit or other real-time voice and audio pipeline systems
• Prior work on conversational AI, voice agents or multi-modal AI products
• Experience with RAG pipelines, LLM evaluation or fine-tuning workflows
• Background in a fast-moving startup or high-velocity product environment

What We Expect

• You take ownership of what you build and don't wait for someone else to fix broken things
• You understand trade-offs and can communicate them clearly to non-engineers
• You think in systems, account for failure modes early and design for graceful degradation
• You leave code and documentation in better shape than you found it

What You'll Get

• End-to-end ownership of features that ship to real users
• Direct influence over technical and architectural decisions
• Work on systems that are used daily by real users
• A small team where your contributions have visible product impact

Ми ПРАЦЮЄМО, щоб мільйони українців впевнено рухались вперед. Тому тут твоя робота справді важлива. Долучайся до команди ОККО, формуймо надійний тил нашої країни разом!

Долучайся до команди ОККО!

Шукаємо AI/ML Engineer!

Приєднуйся, бо ми:

• офіційно і швидко приймаємо на роботу з першого дня;
• не затримуємо зарплату;
• оплачуємо відпустку (24 дні в рік) та лікарняний;
• забезпечуємо безкоштовне медичне страхування для кожного працівника (купівля ліків, лабораторні дослідження, медогляди, амбулаторна допомога та ін.);
• підтримуємо та допомагаємо один одному, адже ОККО — це велика і дружня команда;
• ОККО — це український бізнес, який визначено критично важливим для функціонування економіки та забезпечення життєдіяльності населення України. Наші військовозобов'язані працівники підлягають бронюванню згідно умов, визначених законодавством.

Що треба робити?

• займатися розробкою та впровадженням GenAI рішень:
  • розробляти системи автоматичної обробки документів;
  • реалізовувати knowledge retrieval sysytems з використанням RAG підходів;
  • впроваджувати LLM-based automation;
• будувати end-to-end рішення:
  • реалізовувати повний цикл — від ідеї та прототипу до production;
  • інтегрувати рішення з внутрішніми системами та API;
• працювати з LLM:
  • виконувати prompt engineering;
  • здійснювати fine-tuning / optimization (за потреби);
  • забезпечувати контроль якості та стабільності відповідей;
• займатися розробкою та оптимізацією RAG систем;
• обробляти неструктуровані дані:
  • виконувати парсинг документів (PDF, таблиці, текст);
  • здійснювати витягування та структуризацію даних;
• будувати ML/LLM пайплайни:
  • забезпечувати їх масштабованість і підтримуваність;
  • враховувати latency та cost.
     

Що ми очікуємо?

• сильна база в класичному ML та NLP;
• розуміння принципів роботи LLM та практичний досвід їх використання;
• досвід роботи з LLM: fine-tuning / post-fine-tuning;
• розуміння RAG: базовий досвід побудови RAG-систем;
• впевнене володіння Python та фреймворками для deep learning (наприклад, PyTorch);
• LLM / GenAI: OpenAI, Anthropic, Hugging Face;
• LLM orchestration: LangChain, LlamaIndex або аналоги;
• Vector DB: Pinecone, Chroma або аналоги;
• Досвід із базами даних: SQL, NoSQL;
• базове знання Azure для деплойменту АІ рішень.

Мрія — освітня екосистема для учнів, батьків/опікунів і вчителів, що надихає вчитися та допомагає знайти себе в сучасному світі. Це ініціатива Президента України Володимира Зеленського, яку реалізують Мінцифри та МОН за підтримки Програми EGAP, що виконується Фондом Східна Європа коштом Швейцарії.

Шукаємо AI Engineer, який/яка буде створювати та масштабувати AI-сервіси для мільйонів користувачів освітньої екосистеми. Ви працюватимете над AI-моделями, алгоритмами та інтелектуальними пайпланами обробки даних.
 

Наша команда шукає людину, яка:

• Має досвід роботи у сфері АІ/ML від 3 років
• Має досвід створення агентних AI систем за допомогою langchain, langgraph, llama-index тощо
• Володіє Python на високому рівні; знання PySpark буде перевагою
• Має досвід розгортання AI-сервісів на хмарних платформамах (AWS, Google Cloud, Azure)
• Має розуміння концепцій моделювання даних, сховищ даних та ETL/ELT-процесів
• Має досвід побудови, адаптації та тренування ML моделей, в тому числі LLM
• Знає основи контейнеризації та оркестрації (Docker, Kubernetes)
• Має вищу освіту
   

Буде перевагою:

• Досвід роботи з графовими базами даних (Neo4j тощо)
• Досвід з системами LLM телеметрії, такими як Arize Phoenix
• Досвід створення Front-end застосунків для прототипування
• Досвід роботи з аналітикою
   

Чим ви будете займатися:

• Реалізовувати нові і удосконалювати існуючі АІ-сервіси Мрії
• Проводити EDA на наших джерелах даних та перетворювати їх на корисні датасети
• Проводити експерименти з моделями та тестувати PoC з реальними школами
• Співпрацювати з веб та мобайл командами щодо інтеграції наших сервісів

Що ми пропонуємо:

• Повну зайнятість у проєкті, важливому для майбутнього освіти в Україні
• Роботу в офісі протягом перших двох місяців (є укриття); далі — можливий гібридний графік
• Можливість долучитися до команди професіоналів, які змінюють освітню систему України
• Участь у створенні продукту, що впливатиме на майбутнє покоління
• Вакансія передбачає опцію бронювання

Етапи найму: співбесіда з HR -> технічне інтерв'ю -> кадрова перевірка -> офер
 

Якщо це не для вас, але ви знаєте людину, яка створена для цієї вакансії, — порекомендуйте, будь ласка!