Location: Montréal
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
About The Job:
Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases.
You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings.
As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision.
What you will do
- Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions.
- Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries.
- Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders.
- Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives.
- Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment.
- Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle.
How We Work in Applied AI
- We care about people and outputs.
- What matters is what you ship, not the time you spend on it
- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
- Always ask why. The best solutions come from deep understanding, not from copying what worked before
- We say what we mean. Feedback is direct, timely, and given because we care.
- No politics. Low ego, high standards.
- We embrace an unstructured environment and find joy in it.
About you
- You are fluent in French and English.
- You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field.
- You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, Staff Engineer or Solutions Architect) focused on AI products or enterprise solutions.
- You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation.
- You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale.
- You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus.
- You have strong software engineering skills, including API design, backend/full-stack development, and system architecture.
- You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers.
- You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent.
Ideally, you have:
- Contributed to open-source projects, particularly in the LLM or AI space.
- Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption.
- A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities.
Why joining us?
You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!
Why join us?
You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
leadBenefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks
Location: Paris
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
ABOUT THE JOB
The Applied AI for Defense team is Mistral’s specialized unit dedicated to delivering high-impact, secure AI solutions for institutions and organizations operating in highly regulated and strategic environments. We work hand-in-hand with clients to design, deploy, and maintain AI systems that meet the highest standards of reliability, security, and operational excellence.
Our team combines deep technical expertise with a rigorous approach to compliance and risk management, ensuring that every solution is both cutting-edge and fully aligned with the unique constraints of our partners.
Mistral AI is seeking an Applied AI Engineer to join this team. You will be responsible for the technical design, implementation, and deployment of AI solutions tailored to the needs of critical infrastructure and sovereign institutions. Your work will directly contribute to projects with significant societal and operational impact.
WHAT YOU WILL DO
• Individually deploy AI solutions into production for use cases with significant operational and strategic impact.
• Develop state-of-the-art GenAI applications tailored to the specific needs of sovereign institutions and critical infrastructure, driving technological transformation in collaboration with our customers.
• Work closely with our researchers, AI engineers, and product teams on complex customer projects involving advanced fine-tuning, LLM applications, and contributions to our open-source codebases for inference and fine-tuning.
• Participate in pre-sales discussions to understand the needs, challenges, and aspirations of potential clients, providing technical guidance on Mistral’s products and technologies to diverse stakeholders.
• Collaborate with our product and science teams to continuously improve our offerings based on customer feedback, with a focus on security, compliance, and performance.
HOW WE WORK IN APPLIED AI
• We care about people and outputs.
• What matters is what you ship, not the time you spend on it
• Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
• Always ask why. The best solutions come from deep understanding, not from copying what worked before
• We say what we mean. Feedback is direct, timely, and given because we care.
• No politics. Low ego, high standards.
• We embrace an unstructured environment and find joy in it.
ABOUT YOU
• Fluent in English.
• PhD or Master's in AI, Machine Learning, Computer Science, or related field.
• 2+ years of experience in AI/ML
• Proven track record of leading teams to deliver complex AI projects from prototyping to production.
• Deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale.
• Proficient in Python, PyTorch, and modern AI frameworks (LangChain, HuggingFace). Cloud platforms (AWS, GCP, Azure) and MLOps tools a plus.
• Strong software engineering skills: API design, backend/full-stack development, system architecture.
• Excels in technical communication with technical and non-technical audiences, including executives.
• Thrives in fast-paced collaborative environments and is passionate about mentoring technical talent.
IT WOULD BE GREAT IF YOU
• Have experience with React or other frontend frameworks.
• Have experience with Deep Learning in PyTorch
• Contributed to open-source projects in the LLM or AI space.
• Have experience in customer-facing roles with a focus on enterprise AI adoption.
SECURITY & COMPLIANCE CRITERIA
• Eligibility: must hold citizenship in the target territory (France for now).
• Clearable: must meet all local requirements for high-level security clearance (e.g., no criminal record, fulfillment of national service obligations).
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Location: Palo Alto; New York; San Francisco
Workplace: Hybrid
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
THE ROLE
As an AI Scientist, you will research and develop novel methods to advance the capabilities of large language models. This role exists to push the boundaries of what AI can achieve, enabling Mistral to deliver systems that transform how businesses operate and integrate into daily life.
You will join a team of engineers and scientists focused on building tooling and infrastructure to train, evaluate, and analyse AI models at scale. Your work will span multiple use cases and modalities, from reasoning and code generation to text, image, and speech processing.
The impact of this role is far-reaching, as you will collaborate cross-functionally to ship AI systems that have real-world applications and open-source frontier models for global benefit.
WHAT YOU WILL DO
- Research and develop innovative methods to advance the frontier of large language models.
- Build tooling and infrastructure to enable large-scale training, evaluation, and analysis of AI models.
- Collaborate with scientists, engineers, and product teams to deploy AI systems with tangible real-world impact.
- Design and implement solutions that address complex challenges in AI model development and deployment.
- Contribute to the open-source community by releasing cutting-edge models and tools.
WHAT WE'RE LOOKING FOR
- A strong publication record in a relevant scientific domain, such as machine learning or natural language processing.
- High proficiency as a software engineer in at least one programming language, such as Python, Rust, Go, or Java.
- Hands-on experience with AI frameworks like PyTorch or JAX, or distributed systems such as Ray or Kubernetes.
- A self-starter mindset, with the autonomy to drive projects forward and the ability to work effectively in a team.
- Experience with training large transformer models in a distributed manner.
- Familiarity with the full MLOps stack, including fine-tuning, evaluation, and deployment.
- Experience with audio or speech processing, including input/output and NLP.
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Задачи:
— Разработка и настройка AI-функций продукта
— Работа с LLM, RAG, embeddings и векторными базами данных
— Интеграция OpenAI, Gemini, DeepSeek и других AI API
— Настройка промптов и улучшение качества ответов моделей
— Работа с учебными материалами и базой знаний
— Поддержка серверной части: Linux, Docker, логи, конфигурации и деплой
— Оптимизация скорости работы и стоимости AI-запросов
Требования:
— Опыт работы от 3 до 6 лет
— Уверенное владение Python
— Опыт работы с LLM, RAG и embeddings
— Опыт интеграции AI API
— Понимание FastAPI и REST API
— Опыт работы с Linux-серверами
— Владение Docker, Git, переменными окружения и инструментами работы с логами
— Умение доводить AI-функции до рабочего состояния в продукте
— Будет преимуществом: опыт работы с Qdrant, Pinecone, Weaviate, Chroma, PostgreSQL, Redis, TTS/STT, Telegram Bot API, Mini App, MLOps и компьютерным зрением
Условия:
— Официальное оформление по Трудовому договору или договору ГПХ (с самозанятым, ИП или физическим лицом)
— График работы 5/2
— Рабочий день: 8 часов
— Гибридный формат работы
— Выплата заработной платы два раза в месяц
— Возможность проектной или долгосрочной занятости
— Условия оплаты обсуждаются по итогам собеседования
Адрес:
Астана, улица Сарайшык, 5
MDiet — early-stage HealthTech стартап, разрабатывающий AI-powered платформу, которая помогает снижать количество повторных госпитализаций пациентов. Продукт ориентирован на рынок здравоохранения США. Возможна релокация в США при успешном росте компании, обсуждается индивидуально.
Tech Stack:
• LangGraph + LangChain / Agentic AI
• vLLM + Hugging Face
• PyTorch + PEFT / LoRA / QLoRA
• Vector databases: pgvector, Qdrant, Weaviate, Chroma, Pinecone
• Advanced RAG, Prompt Engineering, Embeddings
• FastAPI + PostgreSQL
• Docker + Kubernetes + async processing: Arq / Celery / Redis Streams
• Apache Airflow для data pipelines
• AWS Cloud: EC2, S3, SageMaker, Lambda, RDS, Bedrock
• Structured output: Outlines / Guidance / Instructor
• Evaluation & observability: Langfuse, RAGAS / DeepEval, Prometheus + Grafana
• MLOps practices
Задачи:
• Проектирование и разработка multi-step LLM agents и pipelines для обработки медицинских данных
• Разработка production RAG-систем с высоким уровнем grounding и качеством citation
• Деплой и оптимизация self-hosted LLM inference через vLLM с фокусом на cost и throughput optimization
• Fine-tuning open-source моделей на domain-specific medical data с измеримым улучшением результата
• Построение data pipelines и versioning для документов, embeddings и training data
• Создание evaluation frameworks, guardrails и систем контроля hallucinations
• Реализация reliable structured output и data extraction
• Тесное взаимодействие с physicians и Platform Architect
Требования:
• Сильный hands-on опыт с production LLM systems: RAG, agents, inference
• Опыт fine-tuning open-source LLMs: LoRA / QLoRA / PEFT, с измеримыми результатами
• Опыт построения data pipelines и versioning для LLM / RAG workloads
• Сильные навыки в evaluation, hallucination reduction и structured output
• Production Python + FastAPI + async processing
• Опыт с self-hosted inference: vLLM или аналогичные решения
• Опыт GPU optimization
• Английский язык на уровне C1: strong written and spoken communication skills
• Bachelor’s degree или выше в Computer Science, Artificial Intelligence, Machine Learning, Data Science или смежной технической области
• 5+ лет опыта в ML/AI
• 1.5–2+ года опыта в production LLM projects
• Опыт с MLOps
Будет плюсом:
• Опыт в medical / clinical NLP или regulated domains
• Cost modeling и optimization of LLM workloads
• MLOps и production fine-tuning pipelines
• Apache Airflow, Prometheus / Grafana или AI Solution Architecture
• Publications in relevant fields
Условия:
• Работа в early-stage HealthTech startup с продуктом для US healthcare market
• Возможность участвовать в создании AI-powered платформы с реальным влиянием на healthcare-процессы
• Офисный формат в Астане первые 7–9 месяцев, далее возможен hybrid/remote
• Зарплата $4 000 – $5 000 USD gross + equity
• Возможность релокации в США при успешном росте компании, обсуждается индивидуально
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Обязанности:
• управлять проектами по разработке агентов: сбирать требования, формулировать метрики качества, согласовывать архитектуру, разрабатывать, проектировать MLOps-пайплайнов
• разрабатывать и внедрять AI-агентов на базе LLM (Python, LangChain, LangGraph, GigaChain)
• интегрировать решения с core-системами банка (REST, Kafka, PostgreSQL).
Требования:
• опыт разработки на Python от 3 лет
• опыт создания backend приложений и разработки API используя веб-фреймворк FastAPI
• опыт работы с PostgreSQL (SQL, индексы, транзакции), SQLAlchemy/asyncpg, Redis
• опыт в разработке и проектировании концептуальной и детальной архитектуры ИТ-решений (PoEE, TOGAF), построения MLOps-пайплайнов (Groovy, Jenkins), понимание базовых принципов MLSecOps, LLMOps
• опыт создания AI-агентов и их внедрения будет преимуществом.
Условия:
• гибридный формат работы (3 дня в офисе)
• годовой бонус и ежегодный пересмотр
• расширенный ДМС с первого дня + стоматологию и льготное страхование для семьи
• корпоративный университет Сбера, внутреннюю образовательную платформу, участие в IT-конференциях
• офис на Варшавском шоссе д.9 с зонами отдыха и спортзалом
• льготную ипотеку в Сбере, корпоративную пенсионную программу, подписку СберПрайм с возможностью совместного использования на трёх близких, скидки от партнеров и сервисов группы компаний.
Задачи:
— Разрабатывать и внедрять классические ML-модели для оценки рисков, выявления мошенничества, прогнозирования оттока и ценообразования.
— Создавать функции на базе больших языковых моделей (LLM) и внутреннюю автоматизацию с использованием RAG-пайплайнов и агентных рабочих процессов.
— Определять стратегию в области искусственного интеллекта, включая стандартизацию инструментов и разработку фреймворков оценки моделей.
— Отвечать за полный жизненный цикл ML: от определения требований заинтересованных сторон до развертывания и мониторинга.
— Сотрудничать с руководителем отдела данных для формирования возможностей ML/AI с нуля.
Требования:
— Опыт профессиональной работы ML-инженером не менее 4 лет с использованием Python в продакшене.
— Глубокие знания классического машинного обучения, включая инженеринг признаков и валидацию моделей.
— Практический опыт работы с фреймворками LLM, такими как LangChain, LangGraph или LlamaIndex.
— Подтвержденный опыт создания систем RAG или продуктов на базе LLM для реальных пользователей.
— Опыт работы с основными облачными провайдерами (AWS, GCP, Azure) и контейнерами.
— Свободное владение английским языком в письменной и устной форме.
Желательно:
— Опыт работы с MLOps-инструментами, такими как MLflow, Airflow или Kubernetes.
— Опыт работы в сферах финтеха, платежей или телекоммуникаций.
Условия:
— Комплексный страховой пакет, включающий медицинское, стоматологическое и профессиональное страхование.
— 30 дней ежегодного отпуска и дополнительная оплата по уходу за ребенком.
— Пособие на оздоровление в размере 5000 SEK и скидки на абонементы в спортзал.
— Пенсионный план и программа бонусов на основе результатов работы.
— Международная и разнообразная команда в Стокгольме.
Обязанности:
- Разрабатывать и внедрять ML-функции для платформы знакомств: рекомендации, поиск, безопасность и антифрод.
- Строить рекомендательные системы и модели совместимости пользователей для повышения качества мэтчинга.
- Разрабатывать NLP-решения для анализа анкет, извлечения структурированных признаков и семантического поиска.
- Реализовывать CV-модели для модерации контента, проверки подлинности фото и выявления AI-generated изображений.
- Создавать модели скоринга рисков, выявления ботов, фейков и мошеннической активности.
- Проектировать полный ML lifecycle: подготовка данных, обучение, оценка качества, деплой и мониторинг моделей.
- Работать в тесной связке с продуктом, backend-разработчиком и QA, участвуя в принятии ключевых технических решений.
Требования:
- Опыт работы ML Engineer от 3 лет и уверенное владение Python.
- Практический опыт вывода ML-моделей в продакшн и поддержки их жизненного цикла.
- Хорошее знание PyTorch или TensorFlow.
- Опыт работы с рекомендательными системами, ранжированием или персонализацией.
- Опыт решения NLP-задач: embeddings, классификация текста, semantic search, retrieval.
- Понимание MLOps-практик: versioning, monitoring, evaluation, CI/CD для моделей.
- Способность самостоятельно принимать технические решения и строить ML-направление практически с нуля.
Будет плюсом:
- Опыт в Computer Vision: модерация контента, face analysis, deepfake detection.
- Опыт создания антифрод- и риск-моделей.
- Опыт работы с LLM, RAG и современными open-source моделями.
- Опыт работы с векторным поиском (Qdrant, FAISS, Weaviate и др.).
- Опыт работы с графовыми моделями и рекомендательными системами.
Условия:
- Участие в развитии продукта с первых этапов;
- Возможность влиять на технические решения и архитектуру системы;
- Минимум бюрократии и быстрый цикл принятия решений;
- Сильную и мотивированную команду;
- Перспективы роста вместе с компанией;
- Удалённый формат работы.
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Senior CV Engineer — Алматы
Опыт от 5 лет
Python, PyTorch, TensorRT, MLOps
Разработка и внедрение CV/ML-решений в production, техническое лидерство.
Junior CV Engineer — Алматы / Астана
Опыт от 1 года
Python, OpenCV, PyTorch/TensorFlow, Docker
Разработка и обучение CV-моделей под руководством опытных инженеров.
Задачи:
- Управление AI-продуктами от идеи до вывода в прод.
- Участие в проработке AI-стратегии кластера (Roadmap, KPI, приоритизация инициатив).
- Проработка архитектуры AI-решений.
- Координация команд: Data Scientists, ML-инженеры, Data Engineers.
- Решение проблем масштабирования моделей и качества данных.
- Запуск PoC и MVP AI-продуктов.
- Оптимизация инференса моделей (скорость, стоимость, точность).
- Дообучение open-source моделей под задачи бизнеса.
Требования:
- Образование: высшее.
- Опыт работы: от 5 лет на релевантной позиции.
- Опыт в предметной области AI.
- Опыт коммерческой разработки, развитый технический кругозор.
- Навыки презентации для C-level с ценностными тезисами.
- Agile/Scrum для ML-проектов.
- Языки: Python, SQL.
- ML/DS: scikit-learn, TensorFlow/PyTorch, Hugging Face, LangChain.
- MLOps: MLflow, Kubeflow, Airflow, Docker/Kubernetes.
- Данные: Spark, DWH (BigQuery, Snowflake), векторные БД (FAISS, Pinecone).
- Опыт управления коллективом: обязателен.
Требования к личным качествам:
- Лидерство, выстраивание коммуникаций, синхронизация работ, критическое мышление, предпринимательский mindset, адаптивность.
Знание стека:
- LangChain, Kafka, K8s, LLM-модели, NLP-модели — embedding, NER, classification.
Location: Warsaw
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
THE ROLE
As an AI Scientist, you will push the boundaries of AI by developing and scaling cutting-edge models. This role exists to advance Mistral’s mission of democratizing frontier intelligence, enabling businesses and consumers to benefit from open, high-impact AI systems. You will collaborate with a global, cross-functional team to design, build, and deploy models that solve real-world problems across reasoning, code, and multimodal applications. Your work will directly shape how AI integrates into daily life and enterprise operations.
What will you do
• Research and develop novel methods to push the frontier of large language models
• Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)
• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
• Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact
What we're Looking for
• You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)
• You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)
• You have high engineering competence. This means being able to design complex software and make it usable in production
• You are a self-starter, autonomous and a team player
Now, it would be ideal if
• You have hands-on experience with training large transformer models in a distributed fashion
• You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment
• You have a strong publication record in a relevant scientific domain
Note that this is not an exhaustive or necessary list of requirements. Please consider applying if you believe you have the skills to contribute to Mistral's mission. We value profile and experience diversity.
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Инновационная AI-платформа анализа геополитических и рыночных данных в реальном времени, обрабатывающая информацию из более чем 2000 первоисточников на разных языках (китайский, арабский, русский и др.).
О роли: Мы ищем опытного Senior Java-разработчика, который возглавит масштабирование и оптимизацию нашего ядра агрегации данных. Вам предстоит проектировать высоконагруженные пайплайны, которые в реальном времени собирают миллионы текстовых данных, отправляют их на обработку нашим AI-моделям трансляции и анализа сентимента, а затем мгновенно доставляют инсайты клиентам.
Основные задачи:
• Проектирование архитектуры: Разработка масштабируемых, отказоустойчивых бэкенд-сервисов на Java;
• Потоковая обработка данных (Stream Processing): Оптимизация систем сбора новостей и рыночных метрик в реальном времени;
• Интеграция с AI/ML: Разработка эффективных API-прослоек для интеграции Java-сервисов с внутренними языковыми моделями (LLM) и инструментами NLP (перевод, извлечение сущностей, анализ тональности);
• Оптимизация производительности: Поиск «узких мест» (bottlenecks), оптимизация работы с базами данных, снижение задержек (low-latency processing).
Наш технологический стек:
• Язык: Java 17+ (Spring Boot / Spring Cloud);
• Big Data & Streaming: Apache Kafka / Pulsar, Apache Flink / Spark Streaming;
• Базы данных: NoSQL (Elasticsearch/OpenSearch для мультиязычного поиска, MongoDB), SQL (PostgreSQL), Кэширование (Redis);
• Инфраструктура: AWS (EC2, S3, EKS), Docker, Kubernetes, CI/CD pipelines.
Что мы ждем от кандидата:
• Опыт: От 5-6 лет коммерческой разработки коммерческого ПО на Java;
• Highload: Уверенные знания concurrency, многопоточности и проектирования систем распределенных вычислений;
• Работа с данными: Глубокое понимание принципов работы очередей сообщений (Kafka) и поисковых движков (Elasticsearch);
• Язык: Английский язык на уровне Upper-Intermediate (B2) и выше для ежедневной коммуникации с распределенной международной командой;
• Плюсом будет: Опыт работы в FinTech / RegTech проектах, парсинге веб-ресурсов или интеграции ML-моделей в продакшн (MLOps).
Что мы предлагаем:
• Гибкость: Полностью удаленный формат работы из любой точки мира;
• Технологически сложный продукт: Работа на стыке Big Data, AI и глобальной рыночной аналитики;
• Влияние на продукт: Минимум бюрократии, плоская структура и возможность напрямую влиять на архитектурные решения;
• Профессиональный рост: Оплата профильного обучения, курсов и участия в международных конференциях;
• Пакет: Конкурентная заработная плата (по результатам технического интервью) + опционы компании (Equity) для ключевых сотрудников.
Задачи:
— Сбор и анализ данных, проведение feature engineering.
— Обучение ML-моделей на табличных данных и их вывод в продакшн.
— Автоматизация пайплайнов сбора данных и моделирования.
— Улучшение ценообразования в ЖД-направлении, автобусах, электричках и аренде авто с помощью ML.
— Подготовка отчетности и презентация итогов работы бизнес-заказчикам.
Требования:
— Опыт работы в Data Science не менее 3 лет.
— Опыт решения задач в ценообразовании, предиктивной аналитике, uplift-моделировании или ранжировании.
— Владение стеком: Python, SQL, ClickHouse, S3, FastAPI.
— Опыт работы с Feature Store / Feast.
Условия:
— Гибкий выбор формата работы: офис, гибрид или full remote.
— Работа в структурированной команде (DS, MLOps, Lead) с использованием OKR для синхронизации целей.
— Регулярные планирования и синки для прозрачности процессов.
— Ценности команды: вовлечённость, инициативность и ответственность.
Location: Krakow, Poland; Krosno, Poland; Lublin, Poland; Poland; Poznan, Poland; Warsaw, Poland; Pilsen, Czechia; Praha, Czechia; Riga, Latvia; Vilnius, Lithuania; Athens, Greece; Crete, Greece; Budapest, Hungary; Miskolc, Hungary; Brussels, Belgium; Liège, Belgium; Mons, Belgium; Namur, Belgium; Sofia, Bulgaria; Bordeaux, France; Grenoble, France; Lille, France; Lyon, France; Montpellier, France; Nantes, France; Paris, France; Toulouse, France; Baden-Baden, Germany; Bad Homburg, Germany; Augsburg, Germany; Aachen, Germany; Bergisch Gladbach, Germany; Berlin, Germany; Bernau, Germany; Bielefeld, Germany; Bramsche, Germany; Chemnitz, Germany; Darmstadt, Germany; Dresden, Germany; Dusseldorf, Germany; Düsseldorf, Germany; Essen, Germany; Frankfurt, Germany; Freiburg, Germany; Geoergsmarienhütte, Germany; Görlizt, Germany; Göttingen, Germany; Greifswald, Germany; Halle, Germany; Hamburg, Germany; Hannover, Germany; Heinsberg, Germany; Karlsruhe, Germany; Kiel, Germany; Koln, Germany; Leipzig, Germany; Leverkusen, Germany; Lingen, Germany; Magdeburg, Germany; Mainz, Germany; Mittenwalde, Germany; Munich, Germany; Münster, Germany; Neu-Ulm, Germany; Neuruppin, Germany; Neuss, Germany; Nuremberg, Germany; Osnabrück, Germany; Paderborn, Germany; Potsdam, Germany; Quedlinburg, Germany; Rimbach, Germany; Rostock, Germany; Schwerin, Germany; Stuttgart, Germany; Ulm, Germany; Varel, Germany; Viechtach, Germany; Warendorf, Germany; Wiesbaden, Germany; Wuppertal, Germany; Lisbon, Portugal; Porto, Portugal; Zagreb, Croatia; Sarajevo, Bosnia and Herzegovina
Workplace: remote
At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an
Senior AI DevOps / LLMOps
specialist
to join one of our
clients
' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.
Key Responsibilities
Automation of Build-to-Production
- Design and implement robust CI/CD pipelines tailored for AI, covering model weights,
dataset versioning, and application code.
- Develop specialized workflows for PromptOps, ensuring that system prompts are
version-controlled, tested for regressions, and deployed with the same rigor as traditional
code.
-Automate the deployment of Agentic workflows, managing the complexities of stateful
AI interactions and multi-agent handoffs.
2. AI Infrastructure as Code (IaC)
- Provision and manage high-performance compute environments (GPU clusters, TPU
pods) using Terraform, Pulumi, or Ansible.
- Define and enforce Policy-as-Code for AI endpoints to ensure compliance with security,
cost-usage limits, and data residency requirements.
- Maintain a consistent environment across Hybrid Infrastructure, ensuring seamless
parity between On-Premises development and Cloud production.
3. Safe Experimentation & Controlled Releases
- Architect Progressive Delivery strategies for AI, including Canary releases, Blue-Green
deployments, and Shadowing (where new models run in parallel with production to
compare outputs).
- Build “Evaluation-in-the-Loop” gates within the pipeline to automatically test for bias,
hallucination, and performance degradation before a release.
- Implement A/B testing frameworks specifically designed for LLM outputs and agentic
behavior.
4. Monitoring & Observability
- Establish deep observability into Inference Endpoints, tracking metrics like tokens-per-
second, latency, and drift in model accuracy.
-Integrate feedback loops that capture production “edge cases” to feed back into the
training and fine-tuning pipelines.
Must-Have Technical Skills:
-Orchestration: Advanced Kubernetes (K8s) skills, specifically with KubeFlow, Ray, or
NVIDIA Triton.
-CI/CD & IaC: Expertise in GitHub Actions/GitLab CI, and Terraform or Pulumi.
- AI Tooling: Experience with Weights & Biases, MLflow, LangSmith, or Arize
Phoenix.
-Hardware: Understanding of GPU virtualization, CUDA drivers, and on-premises
hardware management.
-Security: Familiarity with Open Policy Agent (OPA) and secret management (Vault).
Experience:
- 10+ years in DevOps, SRE, or Cloud Engineering.
- 2+ years of hands-on experience in MLOps or LLMOps, specifically moving LLMs
from notebook to production.
-Proven experience managing Hybrid Cloud environments (e.g., AWS/Azure + Private
Data Center).
Location: Tallinn, Estonia
Are you looking for the next professional opportunity that will challenge you and advance your career?
Join our team now!
Tickmill is looking to hire a
Senior AI/ML Engineer (AI Lead)
to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact.
About Tickmill.
Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options).
Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide.
Our culture is built on trust, transparency, and high standards. We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields.
Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can.
We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth.
Join the Tigers!
What does the role look like?
The Senior AI/ML Engineer (Applied AI Lead) will have the chance to:
• Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments.
• Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact.
• Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management.
• Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies.
• Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts.
• Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact.
• Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations.
• Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness.
• Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery.
• Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery.
What do you need to succeed in this role?
• 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation).
• Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability).
• Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability).
• Hands-on experience with large-scale data processing (Spark / PySpark).
• Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility.
• Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows.
• Strong SQL skills and experience working with large, complex datasets in real-world environments.
• Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements.
• Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems.
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly.
• Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness.
The below are considered as a plus:
• Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions.
• Experience with real-time or streaming ML systems.
• Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data.
• Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards).
• Experience contributing to team standards, mentoring, or leading applied AI delivery.
By joining us, you can expect:
A Unique Opportunity for a career in a global, fast-growing company.
Attractive
remuneration package
based on qualifications and experience.
Opportunities to learn and grow through our “
Employee Training & Development program”.
Stebby Sports Compensation or Confido Health Compensation.
Multiple
events
to bond with the team and the group.
Birthday and Loyalty
benefits
.
What to expect from our recruitment process:
Interview with HR
Assessment task
Interview with hiring managers
Final interview with top management
Make your next Career step and apply NOW!
*Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.
Location: Limassol, Cyprus
Are you looking for the next professional opportunity that will challenge you and advance your career?
Join our team now!
Tickmill is looking to hire a
Senior AI/ML Engineer (AI Lead)
to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact.
About Tickmill.
Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options).
Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide.
Our culture is built on trust, transparency, and high standards. We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields.
Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can.
We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth.
Join the Tigers!
What does the role look like?
The Senior AI/ML Engineer (AI Lead) will have the chance to:
• Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments.
• Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact.
• Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management.
• Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies.
• Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts.
• Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact.
• Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations.
• Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness.
• Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery.
• Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery.
What do you need to succeed in this role?
• 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation).
• Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability).
• Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability).
• Hands-on experience with large-scale data processing (Spark / PySpark).
• Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility.
• Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows.
• Strong SQL skills and experience working with large, complex datasets in real-world environments.
• Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements.
• Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems.
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly.
• Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness.
The below are considered as a plus:
• Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions.
• Experience with real-time or streaming ML systems.
• Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data.
• Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards).
• Experience contributing to team standards, mentoring, or leading applied AI delivery.
By joining us, you can expect:
A Unique Opportunity for a career in a global, fast-growing company.
Attractive
remuneration package
based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance).
Opportunities to learn and grow through our “
Employee Training & Development program”.
Medical Insurance Cover
, which includes Outpatient, Inpatient, and Dental Care.
Multiple
events
to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company.
Participation in our welfare investment and savings plan through our
Provident Fund Scheme.
Birthday and Loyalty
benefits
.
Collaboration with SportBenefit.
What to expect from our recruitment process:
First interview with hiring managers or an HR call
Task Assessment
Technical Interview or home assignment
Final interview with top management
Make your next Career step and apply NOW!
*
Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.
Задачи:
- Пресейлы с потенциальными клиентами
- Подготовка эстимейтов и пропоузалов на скоуп работ
- Прохождение клиентских интервью для старта проектов
- Ведение технической части в проектах: помощь разработчикам в построении изначального решения
- Контроль выполнения работ инженерами и попадание в сроки в соответствии с эстимейтами
Требования:
- Опыт на позиции AI архитектора или аналогичной роли
- Широкий опыт работы с клиентами (преимущественно со стартапами)
- Опыт подготовки оценок для проектов, организация работы и контроль попадания в сроки
- Важен бекграунд в backend разработке, знание Python на уровне senior, опыт с современными библиотеками и фреймворками (особенно FastAPI), опыт проведения код-ревью
- Коммерческий опыт с GenAI, интеграции AI решений в приложения (LLM, RAG, ИИ-агенты и др.)
- Знание популярных инструментов для интеграции AI/LLM в приложение (например, Hugging Face Transformers, LangChain, OpenAI Python SDK, PydanticAI, LlamaIndex, Microsoft AutoGen, Ollama и др.)
- Знание и опыт с CI/CD, DevOps, MLOps
- Если есть экспертиза в конкретном домене в AI (Healthcare, Video, etc.), будет огромным плюсом
- Разговорный английский язык на уровне не ниже B2 (Upper-Intermediate)
- Локация кандидата должна быть вне РФ и вне РБ
Условия:
- Удалённый формат работы
- Гибкий рабочий график, фулл-тайм
- Задачи на стыке бизнеса и современных AI-технологий
- Возможность получить широкую экспертизу в разнообразных доменах бизнеса
- Влияние на развитие продуктов и на технические решения
- Заключаем договор формата b2b (с ИП, валютный расчётный счёт)
Задачи:
- Пресейлы с потенциальными клиентами
- Подготовка эстимейтов и пропоузалов на скоуп работ
- Прохождение клиентских интервью для старта проектов
- Ведение технической части в проектах: помощь разработчикам в построении изначального решения
- Контроль выполнения работ инженерами и попадание в сроки в соответствии с эстимейтами
Требования:
- Опыт на позиции AI архитектора или аналогичной роли
- Широкий опыт работы с клиентами (преимущественно со стартапами)
- Опыт подготовки оценок для проектов, организация работы и контроль попадания в сроки
- Важен бекграунд в backend разработке, знание Python на уровне senior, опыт с современными библиотеками и фреймворками (особенно FastAPI), опыт проведения код-ревью
- Коммерческий опыт с GenAI, интеграции AI решений в приложения (LLM, RAG, ИИ-агенты и др.)
- Знание популярных инструментов для интеграции AI/LLM в приложение (например, Hugging Face Transformers, LangChain, OpenAI Python SDK, PydanticAI, LlamaIndex, Microsoft AutoGen, Ollama и др.)
- Знание и опыт с CI/CD, DevOps, MLOps
- Если есть экспертиза в конкретном домене в AI (Healthcare, Video, etc.), будет огромным плюсом
- Разговорный английский язык на уровне не ниже B2 (Upper-Intermediate)
- Ваша локация должна быть вне РФ, вне РБ
Условия:
- Удалённый формат работы
- Гибкий рабочий график, фулл-тайм
- Задачи на стыке бизнеса и современных AI-технологий
- Возможность получить широкую экспертизу в разнообразных доменах бизнеса
- Влияние на развитие продуктов и на технические решения
- Дружную команду экспертов, обмен знаниями и тех.рост
- Заключаем договор формата b2b (с ИП, валютный расчётный счёт)
УдалённоГеография найма не уточнена
Paris; Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks
ГибридPalo Alto; New York; San Francisco; Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
Warsaw; Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks