Jobs ML / AI

We seek a Strong Middle ML / AI Engineer to join our team on a humanitarian transparency platform. This is a hands-on engineering role focused on building machine learning models and data pipelines — primarily around deduplication, anomaly detection, and statistical analysis of humanitarian data.

 

🧙‍♂️ In This Role You Will

• Design, build, and maintain ML models for deduplication, anomaly detection, and predictive analytics.
• Work with structured humanitarian data — beneficiary records, financial transactions, procurement flows.
• Build and maintain data processing pipelines using Python (Pandas, NumPy, scikit-learn).
• Collaborate with the backend team to expose ML/AI outputs via APIs.
• Monitor model performance and iterate based on real-world feedback.
• Document your work and support knowledge sharing within the team.
  
  
   

🎯 You May Be Interested If

• You enjoy working with messy, real-world data and turning it into reliable ML outputs.
• You care about model quality, reproducibility, and practical impact.
• You're comfortable applying classical ML approaches to solve concrete business problems.
• You're excited to collaborate in a remote, cross-functional environment.
• You value autonomy, clear communication, and working in a supportive, small-team setting.
  
   

👌 Role Requirements

• 3+ years of experience in ML engineering, data science, or a closely related role.
• Strong Python skills: Pandas, NumPy, scikit-learn.
• Experience building and deploying ML models in production environments.
• Solid understanding of data pipeline design and data quality practices.
• Familiarity with cloud platforms (Azure or AWS) for ML workloads.
• Proficiency with Git and standard development tooling.
• English proficiency at B1 level or higher.
   

Nice to have:

• Experience with PyTorch or TensorFlow.
• Hands-on experience with LLM integrations (OpenAI, Anthropic, or similar).
• Familiarity with ML experiment tracking tools (e.g. MLflow, Weights & Biases).
• Experience with GIS or geospatial data.
• Background in fraud detection, entity resolution, or deduplication tasks.
• Familiarity with Docker and CI/CD workflows for ML pipelines.
  
   

💻 Working Conditions

• Employment Type: Full-Time
• This is a fully remote position with the entire team across Ukraine.
• 20 working days of paid vacation per year.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• Flexible working hours to promote a healthy work-life balance.

A Ukrainian-British software company is seeking an ML/Computer Vision Engineer to join their team.

About the product: A spatial data analysis platform tailored for the UK and US markets. The company is successfully adapting MilTech innovations (SLAM/LiDAR) for commercial use.

The challenge: As the project scales from a prototype to enterprise-grade deployment, they need an expert to build the platform's "intelligent core." You will be responsible for creating systems that handle automated 3D change detection and track object conditions over time.

Why apply? This is your chance to translate your expertise in computer vision and 3D reconstruction into a high-impact product with a solid business model in Western markets.
 

Key Requirements:

• Strong background in Computer Vision, 3D Reconstruction, and Object Detection, including hands-on experience in training neural networks from scratch and selecting/curating training datasets.
• Fluency in English (both written and spoken).

Responsibilities:

• Design and build a temporal comparison pipeline: point cloud alignment (ICP, feature-based registration), change detection across aligned spatial models, surface-level condition change classification.

• Build and train a condition scoring model: defect type classification, severity grading.

• Develop a synthetic data generation pipeline from real-world data assets.

• Implement and adapt feature matching architectures (SuperGlue, LightGlue, LoFTR).

• Own model validation against the ground truth dataset: false positive rate, false negative rate.

• Research and evaluate 3D Gaussian Splatting and NeRF-based representations as potential improvements to the point cloud comparison pipeline.

Benefits & Perks:

• Hands-on experience with 3D Gaussian Splatting, NeRF, Master SL (open-source SLAM library), and ARKit.

• 20 working days of paid vacation + 5 paid sick days annually.

• Health insurance matching/compensation and company-provided tech equipment.

• Full-time, 100% remote.

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!

Streamline is a supply chain planning platform, and AI agents are central to where we’re headed. We’re building toward a product that doesn’t just surface recommendations but can increasingly act on them — and the agents our users interact with are at the center of that.

We’re growing toward agents that take on more responsibility over time — moving step by step from co-pilot toward genuinely autonomous behavior. That progression is the core of the problem you’d be working on.

We’re looking for an AI Engineer to help us build it. You’ll work on the agents our users interact with — improving the ones we already have and building new ones — on top of an infrastructure and architecture that’s already in place, which you’ll also help extend and build out.

This is a hands-on role for someone who likes shipping. We’re not after a researcher or a model trainer; we want a strong, product-minded engineer who can take a problem, figure out the right AI approach, and deliver it well. You’ll have real ownership of what you build, and plenty of room to grow as our AI capabilities (and team) expand.

What you’ll do:

• Build and ship in-product AI agents — extending our multi-agent AI Assistant and creating new agents for new use cases
• Work on the progression from co-pilot to autonomy — building agents that take on more responsibility over time, from assisting the user toward handling tasks on their own
• Extend and improve the AI infrastructure — orchestration, context management, tool integrations, retrieval, and evaluation
• Maintain and improve existing AI features
• Set up and improve CI/CD and testing for our AI systems
• Help shape the processes and workflows around how we build and run AI — together with the wider team
• Work closely with the product team on the AI roadmap, bringing ideas for where AI can add the most value

• Keep an eye on a fast-moving field and bring in new tools and techniques where they help

   

Requirements:

• Solid software engineering skills, comfortable working in Python
• Hands-on experience building LLM-powered applications or agents (production experience is a big plus)
• Familiarity with agent frameworks and orchestration (ADK, LangGraph, LangChain, CrewAI, or similar)
• A working understanding of the building blocks of modern AI apps: prompting, tool/function calling, RAG, vector stores, context management
• A sense for how to evaluate whether an AI feature actually works, not just whether it runs
• Comfort with the practical side of shipping: testing, CI/CD, deployment, and being mindful of cost and latency
• A product-oriented mindset — you think about the user and the outcome

• Initiative and ownership — you can take something from idea to shipped without needing to be told every step

   

Nice to have:

• Familiarity with multiple LLM providers (Anthropic, Google, OpenAI)
• Experience steering and configuring agents through instruction/context files (e.g., CLAUDE.md, AGENTS.md)
• A grasp of agent skills and the ability to design and build them
• Experience with agent platforms for building and running multi-agent infrastructure (e.g., OpenClaw or similar)
• Experience with LLMOps / observability tooling (e.g., LangSmith, Langfuse, or similar)
• C++ — our product core is written in C++, so the ability to work with it directly is a real plus
• PostgreSQL (or any relational DB) — schema design, queries, indexing basics
• Docker basics — build and run a container, read a Dockerfile

• Experience in a product / SaaS environment

   

We Offer:

• Medical insurance.
• Friendly and supportive team environment.
• Opportunities for professional and career growth.
• Access to AI-powered tools to enhance productivity and daily work.
• Involvement in a fast-growing project.
• Paid lunch, corporate and team-building events.

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).

We are looking for a Senior ML Computer Vision Engineer to join our team!

Our client is an innovative technology division within one of the world's top-10 copper producers. You'll play a pivotal role in their expanding Computer Vision and AI ambitions. While the initial focus involves advanced asset management, the team is embarking on a long-term journey to leverage traditional machine learning, artificial intelligence, and predictive maintenance across their global operations.

Working closely with a newly appointed Computer Vision Subject Matter Expert (SME) and cross-functional data and integration teams, you will drive research and development initiatives from proof-of-concept through to production. Your work will directly shape how the organisation utilizes visual and operational data, eventually integrating these cutting-edge AI capabilities into the core asset management scope and broader operational ecosystem.

Responsibilities:

• Partner with the Computer Vision SME to drive R&D initiatives, exploring new applications for AI, CV, and traditional machine learning within heavy industry.
• Design, develop, and deploy Computer Vision models (e.g., object detection, image classification, segmentation) and traditional ML algorithms for predictive maintenance and asset monitoring.
• Translate business requirements and R&D concepts into scalable, production-ready machine learning pipelines.
• Collaborate with Data Engineers and Analytics Engineers to ensure seamless ingestion, transformation, and availability of visual, sensor, and operational data.
• Work alongside Integration Engineers to embed AI/ML capabilities and model outputs into existing enterprise applications and asset management systems.
• Implement MLOps best practices for model training, versioning, deployment, monitoring, and lifecycle management within an Azure-centric environment.
• Evaluate and select appropriate algorithms, frameworks, and cloud-native AI tools to meet evolving business and performance needs.
• Prepare comprehensive technical documentation, model architectures, and performance reports for technical and non-technical stakeholders.

Requirements:

• 5+ years of hands-on experience as a Machine Learning Engineer, Computer Vision Engineer, or AI Researcher in a software development environment.
• Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• Proven experience building and deploying Computer Vision solutions (e.g., using OpenCV, YOLO, ResNet) in real-world scenarios.
• Solid foundation in traditional machine learning techniques (e.g., scikit-learn, XGBoost) and statistical data analysis, particularly for predictive maintenance or time-series forecasting.
• Experience with cloud-based ML platforms and MLOps practices, preferably utilizing Azure Machine Learning, Databricks, or similar enterprise environments.
• Familiarity with data manipulation and analysis libraries (Pandas, NumPy) and working with large, diverse datasets (images, video streams, sensor data).
• Strong analytical and problem-solving skills, with a track record of transitioning models from R&D phases into production scale.
• Excellent communication skills, with the ability to collaborate effectively with SMEs, data engineering teams, and business leadership.
• Master’s degree or PhD in Computer Science, Artificial Intelligence, Data Science, or a related highly quantitative field (or equivalent applied experience).

Nice to have:

• Background in mining, heavy industry, or manufacturing environments, particularly working with OT (Operational Technology) or IoT sensor data.
• Experience processing and analyzing geospatial data, drone imagery, or edge-computing AI deployments.
• Familiarity with Azure Data Factory, Azure Synapse, or Azure Integration Services to better align with the broader data platform team.

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

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Computer Vision Engineer to join a project with a global leader in biomedical imaging. The company offers a comprehensive product portfolio for Karyotyping, H&E, IHC, and FISH analysis, providing advanced imaging and analysis tools for Pathology, Cytogenetics, and Research laboratories. This role involves working on cutting-edge solutions that enable high-precision diagnostics and support innovation in scientific research.

Key Requirements:

🔹 5+ years of hands-on experience in algorithm development using Python (must) and C++ (advantage);
🔹 Proven experience in training, fine-tuning, and deploying AI/ML models – Must;
🔹 Experience in Computer Vision (e.g., Shape Analysis) / Image Processing using image processing libraries like OpenCV in C++ – Advantage;
🔹 Strong ability to work independently as well as in a SCRUM team under Agile dynamic environment; proactive and self-driven;
🔹 Methodical, solution-oriented mindset with a strong “can-do” approach;
🔹 MSc or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Physics, or a related field – Must;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Research and develop advanced algorithms in Machine Learning, Neural Networks, Computer Vision, Image & Signal Processing, to be integrated into ASI products;
🔹 Define software specifications and deliver production-ready code that meets project milestones, while addressing constraints such as computational resources, response time, and memory consumption (GPU and CPU);
🔹 Train, optimize, validate and Integrate AI/ML models for diagnostic and imaging applications using Python and its libraries (PyTorch, NumPy, etc);
🔹 Collaborate closely with cross-functional teams, including R&D, Applications, and Product groups;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;
 

Backend AI Engineer

[Freelance, Full-time, Remote]

SNEAK PEEK

⇨ Location: Remote, GMT+0/+4

⇨ Interview process: HR Interview ⇨ Technical interview ⇨ Take-home challenge ⇨ Presentation of home challenge 

WHO ARE WE? 

At Rounds, we believe in harnessing the power of cutting-edge technology to drive business success. Our transformative, machine-learning technology identifies and optimizes mobile assets, while our team of experts, with their unparalleled human capital and business acumen, provides the strategic direction and support to turn mobile assets into profitable businesses. Together, we are revolutionizing the mobile industry. 

THE ROLE

We’re looking for a strong systems-oriented engineer with hands-on LLM experience to join our AI Innovation team. In this role, you’ll build AI systems and internal products that improve how teams work across different departments and areas in the company. The common denominator is ownership: you should be comfortable leading projects end-to-end, including clarifying needs with stakeholders, making decisions under ambiguity, and pushing through blockers when they arise.

This role is a strong fit for someone who enjoys both sides of applied AI work: full-stack engineering and practical use of LLM capabilities.

Hiring manager: Ori Nahum, AI Innovation Team Lead 

What you’ll be working on

Examples of projects you may work on:

• AI agents for code generation workflows (especially in mobile applications)
• A mobile app navigation agent
• Backend services that orchestrate LLM workflows, tool calling, and integrations with internal systems
• AI chatbot connected to internal data sources and business systems
• And other new AI-driven solutions that support different departments across the company

You’ll be expected to move between experimentation and implementation: validating ideas quickly, turning the promising ones into reliable tools, and leading projects far enough to make them useful in practice, not just technically possible.

WHAT ARE WE LOOKING FOR?

Must-have

• 5+ years experience in software development (preferably in Python, TypeScript, or mobile development).
• Ability to lead projects from idea to production, including aligning with stakeholders, driving decisions, and proactively removing blockers when needed
• Hands-on experience building LLM-based products, tools, or agents beyond toy prototypes
• Good understanding of prompt design, tool calling, orchestration, and how to make LLM systems actually useful
• Strong English communication skills

Big advantage

• Experience building internal developer tools or productivity systems
• Background in mobile development, especially native Android or iOS
• Design and implement evaluation frameworks to assess AI performance, accuracy, and reliability.
• Solid understanding of ML theory and how LLMs work under the hood, including key concepts, limitations, and trade-offs beyond the API layer
• Familiarity with cloud infrastructure / DevOps / CI-CD
• Good judgment around where AI adds value and where it doesn’t

Who will do well here

You’ll likely do well in this role if you:

• Like building practical systems, not just demos
• Take initiative without waiting for perfect specs
• Enjoy exploring new tools, but know how to separate hype from what’s actually useful
• Want the freedom to research, experiment, and then ship
• Enjoy working across different problem spaces and use cases, rather than staying in one narrow lane

INTERESTED?

Our recruitment process consists of the following steps: 

• HR interview with the recruitment manager: 45 min
• Technical interview with the AI Engineer Tech Lead & Team Lead: 1 hour
• Take-home challenge: ~ 4 hours of work
• Final Interview - take-home challenge presentation with CTO and AI Engineer Team Lead and Tech Lead: 1 hour

About the Role

The company is seeking a Creative AI Specialist with strong motivation, curiosity, and a passion for learning. This role is ideal for someone early in their career who wants to grow at the intersection of design, marketing, AI, and product. This position focuses on creating assets that perform, learning fast, and becoming part of a team building next-generation creative workflows. You will design and generate CRM and marketing creatives using a combination of traditional design tools and emerging AI workflows, working closely with Customer Success, Product, internal teams, and clients to test, iterate, and improve creative and product performance. This is a client-facing role requiring excellent English communication skills and availability to work during US time zone hours.

Responsibilities

• Create email and CRM assets at scale
• Design visuals for social media and lifecycle campaigns
• Learn and apply AI-driven creative workflows, including prompting, iteration, and automation
• Use tools like ComfyUI and other AI platforms to generate and refine visual content
• Support A/B testing processes and optimize creatives based on performance data
• Translate briefs into clear, compelling visual solutions
• Communicate directly with clients to understand briefs, gather feedback, clarify requirements, and support creative execution
• Participate in client-facing workflows, including creative reviews, iteration cycles, and campaign-related discussions
• Collaborate closely with Customer Success, Product, and internal teams to improve creative and product performance
• Operate effectively during US time zone working hours to support client needs and internal collaboration
• Balance speed and quality in a fast-paced environment

• Continuously learn new tools, workflows, and product capabilities

   

Requirements

• 3–5 years of experience in graphic design, marketing design, or creative roles — or exceptional junior talent with a strong portfolio
• High-level English, both written and spoken
• Strong client-facing communication skills and comfort working directly with customers
• Ability to manage feedback, clarify requirements, and communicate creative decisions professionally
• Availability to work during US time zone hours
• Strong motivation to grow in the worlds of AI, product, and performance marketing
• Curiosity and eagerness to learn new tools quickly
• A proactive, hands-on startup mentality
• High level of visual taste and attention to detail
• Ability to move fast, adapt, and solve problems independently
• Data-driven mindset — you care about outcomes, not just aesthetics
• Strong communication skills and ability to work with clients and cross-functional teams
• Background in advertising or performance marketing — an advantage

• Prior experience with AI tools — a plus, but not required

   

About the Company

The company is a fast-growing technology company building AI-powered solutions for marketing and customer engagement. Its platform helps brands create, optimize, and scale personalized creative content across lifecycle and CRM channels using modern AI workflows and data-driven processes. The company operates at the intersection of creativity, performance marketing, and product technology, working with international clients and rapidly evolving tools.

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.

We are looking for a Lead/Senior AI/ML Engineer to join our team!

Our client is an innovative technology division within one of the world's top-10 copper producers. The team focuses on leveraging AI, machine learning, and advanced analytics to optimize industrial operations, improve asset reliability, and support data-driven decision-making across global mining and production facilities. The role is focused on building intelligent solutions for predictive maintenance, anomaly detection, and asset performance optimization, helping reduce downtime and improve operational efficiency across large-scale industrial environments.

Part-time work is also possible (4 hours a day).

Responsibilities:

• Design, develop, and deploy machine learning models for predictive maintenance, anomaly detection, and asset health monitoring.
• Build and maintain production-grade ML pipelines for time-series forecasting and sensor/telemetry data processing.
• Collaborate with Data Engineers and Analytics Engineers on data preparation, feature engineering, and model integration.
• Integrate model outputs, risk scores, and predictive insights into operational dashboards and business applications.
• Establish and maintain MLOps processes, including model deployment, monitoring, retraining, and drift detection.
• Research and evaluate new AI/ML approaches, tools, and technologies to improve predictive capabilities and business outcomes.
• Work closely with business and technical stakeholders to translate complex analytical results into actionable recommendations.

Requirements:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• Strong Python skills and hands-on experience with Pandas, NumPy, Scikit-Learn, SciPy, and related ML libraries.
• Proven experience with time-series forecasting and predictive modeling techniques (ARIMA, Prophet, XGBoost, LSTM/RNN, etc.).
• Experience working with telemetry, IoT, sensor, or equipment performance data.
• Hands-on experience with Azure Machine Learning, Databricks, MLflow, or similar MLOps platforms.
• Strong SQL skills and experience working with both relational and non-relational databases.
• Experience building and deploying production-ready ML solutions.
• Strong analytical and problem-solving skills with the ability to translate technical insights into business value.

Nice to have:

• Master's or PhD degree in Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• Experience in mining, manufacturing, heavy industry, utilities, or other asset-intensive domains.
• Knowledge of Operational Technology (OT) environments and reliability engineering concepts.
• Experience with enterprise asset management systems such as SAP PM or IBM Maximo.
• Familiarity with reliability methodologies such as RCM or FMEA.
• Experience with real-time data processing and anomaly detection on streaming platforms (Kafka, Azure Stream Analytics, etc.).

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

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

We're looking for someone who is genuinely excited about AI and wants to help others use it better.

At LITSLINK, we already have AI/ML engineers working on client projects. However, we're looking for a person who will help grow our AI expertise across the company, support client-facing activities, share knowledge internally, and become one of the key AI advocates within the organization.

This role sits at the intersection of AI, business, education, and consulting.

What You'll Do

• Participate in AI-related presales activities and client meetings
• Help clients identify opportunities where AI can create real business value
• Stay up to date with the latest AI trends, tools, frameworks, and technologies
• Organize internal AI workshops, demos, and knowledge-sharing sessions
• Help teams adopt AI tools and improve their workflows
• Research, test, and evaluate new AI products and approaches
• Collaborate with AI/ML engineers and help distribute knowledge across the company
• Support internal AI initiatives and contribute to the growth of our AI practice
• Mentor and support team members who are exploring AI technologies
   

What We're Looking For

• Strong interest in AI and emerging technologies
• Understanding of modern AI concepts such as LLMs, AI Agents, RAG, MCP, AI Automation, and related technologies
• Technical background and understanding of software development processes
• Excellent communication and presentation skills
• Ability to explain technical concepts to both technical and non-technical audiences
• Experience working with AI tools in practice
• Upper-Intermediate or higher English level
   

Nice to Have

• Experience participating in presales or discovery sessions
• Experience conducting workshops, trainings, webinars, or presentations
• Background in AI/ML, Business Analysis, Product Management, Solution Architecture, Technical Writing, or Consulting
• Experience in outsourcing or consulting environments
• Personal AI projects, public speaking, blogging, or community involvement
   

Why This Role Is Different
This is not a traditional AI Engineering position.
You won't spend all day training models or writing production code.
Instead, you'll help shape how AI is adopted across teams, support client conversations, explore new technologies, share knowledge, and help both colleagues and clients navigate the rapidly evolving AI landscape.

If you're the type of person who constantly tests new AI tools, follows industry updates, and enjoys helping others understand and use AI more effectively, we'd love to talk to you.

The best way to have an exciting and unique experience at sports and music events is with official hospitality packages and VIP tickets.

The product company is searching for an AI Engineer for a full-time remote.
It's a trusted online marketplace where fans can buy and sell official hospitality packages and VIP tickets to live sports, music, and cultural events.

You’ll help shape the future of customer-facing AI applications, from conversational sales agents to real-time support copilots, transforming how fans discover, explore, and purchase unforgettable live event experiences.

The company has:
— Excellent rating on Trustpilot (4.9),
— Partnerships with the best clubs, venues, and artists,
— Traffic of around 280K monthly unique users per month and growing fast,
— Currently focused on the UK market, but poised to enter European markets in the near future.

Must have experience in Python development, experience in developing and deploying custom LLM agents, experience with MCP and RAG.