Вакансии

Задачи: — Выявление производственных проблем и точек роста на основе данных; — Участие в обследовании производственных участков, выезды в цеха, изучение технологических процессов на месте; — Формализация производственных задач в цифровые кейсы: прогнозирование, классификация, детекция отклонений, контроль качества, оптимизация режимов; — Сбор, выгрузка, очистка и консолидация данных из производственных и корпоративных информационных систем; — Анализ данных технологических процессов, поиск закономерностей, факторов влияния и причин отклонений; — Разработка, обучение и валидация ML-моделей для прогнозирования, оптимизации и поддержки принятия решений; — Разработка и внедрение CV-решений; — Подготовка датасетов, разметка данных, организация процессов сбора и актуализации обучающих выборок; — Проверка гипотез, проведение пилотных проектов и оценка экономического эффекта; — Визуализация результатов анализа, подготовка отчетов и рекомендаций для производственных подразделений; — Взаимодействие с внутренними заказчиками, подрядчиками, интеграторами и смежными командами. Требования: — Практический опыт разработки и внедрения решений на базе ML; — Практический опыт разработки и внедрения решений на базе Computer Vision; — Опыт работы с производственными данными, временными рядами, журналами событий, технологическими параметрами; — Опыт полного цикла работы с данными: сбор, выгрузка, очистка, анализ, построение признаков, обучение моделей, внедрение; — Опыт проведения обследований производственных процессов и интервью с внутренними заказчиками; — Понимание специфики промышленного предприятия и готовность работать “в поле”; — Желателен опыт работы в металлургии, горнодобывающей промышленности, тяжелой промышленности, химическом производстве или энергетике; — Понимание технологических процессов агломерационного, коксового или доменного производства будет преимуществом; — Уверенное владение Python и библиотеками для ML/CV; — Знание методов регрессии, классификации, кластеризации, поиска аномалий, анализа временных рядов, оптимизации, глубокого обучения; — Опыт построения CV-моделей; — Опыт работы с SQL и промышленными базами данных (MES, ERP, SCADA, historians, лабораторные системы, систем АСУ ТП); — Понимание принципов интеграции моделей в промышленный ИТ-ландшафт; — Опыт работы с Docker, Git, MLOps-инфраструктурой; — Применение LLM в разработке решений; — Понимание производственных показателей: качество сырья и продукции, производительность, простои, расход топлива и энергоресурсов, стабильность технологических режимов, надежность оборудования; — Понимание причинно-следственных связей в производственном процессе и умение переводить экспертные знания технологов в аналитические модели; — Навык оценки экономического эффекта от цифровых инициатив: снижение потерь, снижение брака, снижение простоев, рост производительности, снижение расхода ресурсов. Условия: — ДМС, включая стоматологию; — Страхование жизни и страховка для путешественников; — Корпоративная мобильная связь; — Система скидок для сотрудников НЛМК ИТ; — Частичная компенсация питания в корпоративных столовых; — Возможность обучения за счет работодателя; — Активная корпоративная жизнь; — Поддержка от компании в жизненно важных событиях; — Бесплатный доступ к электронной библиотеке.

Location: Beograd, Serbia Workplace: hybrid About the role We’re looking for a highly autonomous Senior Data & ML Engineer who wants to be the true owner of how data works for the teams they support, delivering solutions completely end-to-end, from initial scoping and design through to delivery, implementation, and full business adoption. Operating with full autonomy, you will work directly with both commercial stakeholders (Product, Finance, Operations, Compliance, and Marketing) and engineering teams. You will translate complex needs into well-defined and well-modelled data products, using scalable processes and pipelines, ensuring those solutions are trusted, documented, and actively used to drive business value. Beyond foundational data architecture, you will support and lead machine learning engineering efforts. You will lead machine learning engineering efforts by transitioning predictive models into production. This involves building the infrastructure, automated MLOps pipelines, and serving architectures required to deploy, monitor, and maintain machine learning solutions at scale. What You’ll Be Doing Data Engineering and Platform Design, build, and maintain data pipelines and transformations on Databricks using Python, PySpark, and SQL. Deploy, operationalize, and monitor machine learning models (MLOps) in production environments. Build and maintain data marts as the primary source of truth for key business domains. Apply data modelling practices (e.g., dimensional modelling, medallion architecture) to maintain data consistency and reusability. Implement data quality checks, monitoring, and alerting. Optimise pipeline performance and cost-efficiency. Lead and actively contribute to engineering standards and process improvements across the data team. Ownership and Stakeholder Management Act as the primary data partner for specific business areas, understanding their processes, goals, and pain points. Deliver end-to-end solutions, managing scoping, discovery, design, delivery, user adoption, and iteration. Gather and translate business requirements into technical solutions. Communicate with engineering peers and commercial stakeholders to define priorities and manage trade-offs. Identify opportunities where data or machine learning can improve decisions, efficiency, or customer outcomes. Enablement and Self-Service Build and maintain datasets that power reporting and dashboards in Preset. Onboard and support users on Preset to promote data self-sufficiency. Promote data practices, including data definitions, documentation, and governance. What You’ll Need to Be Successful 5+ years of experience as a Data/ML Engineer, with a track record of independently owning data/ML solutions from scoping to adoption. Proficiency in Python, SQL, and PySpark/Spark. Experience with modern data platforms, such as Databricks (Delta Lake, Unity Catalog, MLflow, workflows). Stakeholder management skills, with the ability to navigate commercial and engineering discussions, manage expectations, and drive cross-functional decisions. Data modelling skills and experience designing data marts for analytics and reporting. Experience building production pipelines with orchestration, testing, monitoring, and version control. Experience with BI tools (e.g., Preset, Tableau, Metabase, Power BI) and data usability principles. Demonstrated accountability for project outcomes and commercial impact. Clear, structured communication in English. Nice to Have Experience in ML Engineering, including deploying machine learning models to production, maintaining MLOps pipelines, and integrating models into data platforms. Experience in fintech, financial services, or payments, particularly regarding transaction, reconciliation, settlement, or regulatory reporting data. Experience with sensitive or regulated data and an understanding of data privacy and governance (e.g., GDPR). Experience with infrastructure as code (Terraform/Tofu), cloud platforms (AWS, Azure, or GCP), and data engineering CI/CD. Experience mentoring engineers or analysts. Interest in applying AI tools to improve data engineering productivity and quality. Why Join Paysend? Make a Global Impact: Join a company that is transforming how people and businesses move money around the world. Your work will contribute to products and services that help millions of customers stay connected globally. Own Meaningful Outcomes: We empower our people to take ownership, make decisions, and drive real impact. You'll have the opportunity to shape solutions, challenge the status quo, and see the results of your work firsthand. Grow with Us: As a fast-growing global fintech, we offer opportunities to learn, develop new skills, take on new challenges, and advance your career across functions and geographies. Collaborate with Exceptional People: Work alongside talented colleagues from diverse backgrounds and disciplines who are united by a shared ambition to build, innovate, and deliver great outcomes for our customers. Move Fast and Make Things Happen: We value action, curiosity, and continuous improvement. You'll be part of a culture that encourages experimentation, embraces change, and focuses on delivering meaningful results. Be Part of Our Journey: We're building the future of the global money movement. Join us at an exciting stage of growth where your ideas, expertise, and contributions can help shape what's next.

- Отвечать за AI-направление студии: определять, какие процессы и как автоматизировать, расставлять приоритеты и доводить решения до реального эффекта; - Курировать и контролировать работу ИИ-помощников для разных направлений (геймдизайн, нарратив, разработка, продюсирование);

webAI is looking for a Senior DevOps Engineer to design, build, and scale secure infrastructure for AI workloads across cloud and edge environments.

🧩 Требования: глубокая экспертиза в одном из направлений — MLOps, Streaming или проектирование архитектуры хранилищ данных с нуля; от 4 лет коммерческого опыта в роли Data Engineer/ETL‑разработчика;

Разработка и развитие компонентов ML-платформы и инфраструктурных сервисов. Автоматизация процессов запуска, сопровождения и мониторинга ML/HPC workloads.

Location: Hong Kong or Remote Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company’s award-winning active play system, is purpose-built to get families moving year-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE+ COPPA compliant and built to support healthy, active play for all ages and abilities. Nex Playground features a growing library of 50+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company’s Most Innovative Companies, TIME’s Best Inventions, and Parents’ Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back? , as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations. Nex employees may be expected to collaborate with colleagues across different time zones. Depending on the role and location, occasional travel may also be required for company events, external meetings, and other business-related activities. Important Notice: ⚠️ To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc . If you receive a suspicious email or message, please do not respond and report it immediately to us. Location: Hong Kong or Remote Type: Full Time The Role As a ML Researcher at Nex, you will develop new machine learning models and algorithms that push the boundaries of computational perception and interaction on Nex Playground. You will join a small, deeply technical team that combines research and engineering to solve complex problems in sensing, understanding, and multimodal interaction. The ML Research role emphasizes rapid experimentation, exploring new ideas and methods to expand what our platform can sense, understand, and respond to. You will work within the ML Research group, collaborating closely with ML Engineers who build the infrastructure that accelerates your research. This role is ideal for researchers who want to see their work directly impact product capabilities while maintaining a focus on cutting-edge innovation. The Mindset You are driven by curiosity and technical discovery. You see research as a systematic process of exploration and validation, not just theoretical work. You balance scientific rigor with practical impact, knowing that the best research solves real problems. You thrive in a team that values experimentation velocity and measurable technical improvement. What You’ll Do Develop novel ML models and algorithms for computational perception and interaction Design and execute rapid experiments to validate new ideas and methods Explore advancements in computer vision, audio processing, sensor fusion, or related domains Collaborate with ML Engineers to integrate research outcomes into training pipelines and production systems Measure and track experimentation velocity, the number and quality of validated experiments per quarter Contribute to research planning and help define the technical roadmap alongside the Engineering Manager and Tech Lead Document research findings and communicate technical progress to the broader team Must Have 2+ years of hands-on ML research experience in industry, academia, or research labs Demonstrable track record of designing and conducting ML experiments from hypothesis to validation Proficiency in Python for ML research and experimentation Deep expertise with PyTorch or TensorFlow for model development Experience training and evaluating ML models on real datasets Understanding of model evaluation metrics, experimental design, and statistical validation Familiarity with data preprocessing, augmentation, and management for ML workflows Experience presenting research findings to technical audiences Nice To Have Expertise in real-time inference, model optimization, or efficient architectures Experience with self-supervised learning, few-shot learning, or foundation models Background in multimodal learning combining vision, audio, and sensor data Contributions to open-source ML projects or released research code Experience collaborating with engineers to productionize research outcomes Familiarity with ML Engineering practices: training pipelines, experiment tracking, MLOps Background in edge computing, on-device ML, or resource-constrained environments Experience with sensing technologies: cameras, microphones, IMUs, or haptic systems Knowledge of privacy-preserving ML, federated learning, or on-device data processing We Offer Competitive compensation package. Flexible working hours and vacation policy. Product-driven culture that treasures talents and individual growth. Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field Nex is located in San Jose, California, USA and Hong Kong . Learn more about us at https://www.nexplayground.com/about . We encourage applications even if you don’t meet more than 50% of the requirements — we believe that experience comes in many forms! Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination. We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.

Location: Brussels, Belgium We currently have a vacancy for a Senior LLMOps Engineer fluent in English, to offer his/her services as an expert who will be based in Belgium. The work will be carried out either in the company’s premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team. Your tasks: Design, build, and maintain production-grade ML systems with a strong focus on Large Language Models (LLMs) in a secure hybrid on-prem / cloud infrastructure; Deploy, test, manage and monitor ML models in different containerized environments; Work closely with data scientists and back-end developers to build, test, integrate and deploy ML models; Evolve the LLMOps lifecycle: data preparation, fine-tuning, evaluation, deployment, monitoring, and iteration. Develop evaluation frameworks for LLM quality, robustness, and regression tracking; Analyse performance metrics and troubleshoot issues to ensure high availability and reliability; Design CI/CD pipelines, use orchestration solutions and data versioning tools; Creating automated anomaly detection systems and constant tracking of its performance and optimizing ML pipelines for scalability, efficiency and cost-effectiveness; Provision of security studies, security assessments or other security matters associated with information system projects; Provision of support and guidance to other team members on LLMOps/MLOps practices. Requirements University degree in a relevant field such as Computer Science, Information Technology, or Systems Engineering combined with relevant IT professional experience of at least 10 years; Excellent experience of managing an on-prem and/or cloud LLM / MLOps infrastructure; Experience with data analytics over big datasets, non-structured databases as well as data lakes; Experience with monitoring and logging tools (e.g. ELK stack, Prometheus, Grafana, OpenTelemetry, Cloudwatch); Experience with model testing and model validation in production environments; In depth knowledge of containerisation and orchestration platforms (e.g. Kubernetes, Docker, Podman, EKS, PKS); Good knowledge of MLflow, TensorFlow (TFX) or equivalents; Good knowledge of Airflow; Good knowledge of AWS or EU cloud providers; Good knowledge of Python; Good knowledge of Unix and Bash; Good knowledge agile software development methodologies; Good knowledge of infrastructure as code (Terraform, CloudFormation); Excellent knowledge of messaging services and platforms (e.g. Kafka, Redis, RabbitMQ); Knowledge of NoSQL databases, such as OpenSearch, MongoDB as well as query languages, such as SQL, Hive, Pig, etc. and with information extraction; Excellent command of the English language. Benefits If you are seeking a career in an exciting, dynamic and multicultural international environment with exciting opportunities that will boost your career, please send us your detailed CV in English, quoting reference (158837/10/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. You may also consider all our other open vacancies by visiting the career section of our web site ( www.eurodyn.com) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS ( www.eurodyn.com) is a leading European Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, age, national origin, ethnicity, gender, disability, sexual orientation, gender identity or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in www.eurodyn.com/privacy. By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorise ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

разрабатывать с нуля AI-агентов и микросервисы для AI-продуктов. исследовать и внедрять новейшие технологические решения в ИИ - Claw-like & Ouroboros.

Location: Санкт-Петербург ИТ B2C — самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее. Ждем именно тебя! Обязанности * проектировать и разрабатывать LLM-workflow, AI-агентов и мультиагентные системы: настраивать взаимодействие моделей, работу с контекстом и вызов внешних инструментов * разрабатывать и улучшать RAG-решения: подготовку данных, векторизацию, поиск релевантной информации и формирование контекста для LLM * исследовать и применять подходы на основе Transformer и Attention для обработки текстов, извлечения сущностей и построения векторных представлений * интегрировать AI-решения со смежными банковскими продуктами и внешними сервисами * проводить эксперименты, оценивать и улучшать качество агентов и ML-моделей, настраивать мониторинг их работы * участвовать в построении масштабируемых MLOps-процессов для развёртывания и стабильной работы моделей в промышленной эксплуатации. Требования * опыт работы в машинном обучении от трёх лет, наличие реализованных и внедрённых решений * практический опыт разработки LLM-workflow или агентских систем, их интеграции и адаптации под бизнес-задачи * опыт работы с RAG и векторным поиском: разбиение данных на фрагменты, выбор embeddings, поиск и ранжирование результатов * знание основ машинного обучения и основных архитектур Deep Learning, в особенности Transformer и механизма Attention; понимание принципов работы и обучения LLM * уверенное владение Python, NumPy, Pandas, Scikit-learn и PyTorch, опыт написания кода для промышленной эксплуатации * опыт работы с LangGraph или аналогичными инструментами построения LLM-workflow и агентских систем * опыт работы с Big Data-стеком – Spark, Hadoop, Hive; умение строить и оптимизировать пайплайны обработки данных * базовые знания и практический опыт в MLOps: развёртывание, мониторинг и сопровождение моделей * умение оценивать качество решений, анализировать ошибки и делать обоснованные выводы по результатам экспериментов * самостоятельность, проактивность, ориентация на результат и готовность осваивать новые подходы. Будет плюсом: * опыт применения GigaChat, Kandinsky и аналогичных моделей в продуктах * опыт решения задач персонализации и разработки рекомендательных систем * опыт использования AI-инструментов для анализа, генерации контента и автоматизации рабочих процессов. Условия * комфортный современный офис * возможность выбрать удобный график – офис/гибрид * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Allen Control Systems is looking for a Director of Computer Vision and Machine Learning to lead perception and tracking strategy, manage teams, and deliver production computer vision and machine learning systems.

Location: Москва Наша команда строит Единую агентскую платформу. Enterprise harness – это окружение: среда и набор инструментов, который обеспечивает безопасную и контролируемую работу агента, использование инструментов и навыков, контролирует права, память, контекст, лимиты, аудит и безопасность. В рамках агентской платформы вам предстоит разрабатывать и внедрять инструменты для окружения агентов. Мы адаптируем лучшие мировые практики, а также сотрудничаем с RnD-командами для пилотирования новых разработок на агентах Банка. Примеры направлений, которыми мы занимаемся: * SkillOpt: автоматическая эволюция навыков агентов на основе трейсов и оценки LLM-as-a-Judge; * Memory-as-a-Service: централизованный сервис памяти для агентов; * AutoJudge: инструмент для подбора судей и метрик для оценки качества работы агентов. Обязанности * Развитие GenAI сервисов: Создание и улучшение RAG-систем (в т.ч. Agentic RAG), инструментов Agent Observability, сервисов обработки документов * обучение моделей: тренировка и дообучение мультимодальных моделей на русском языке (OCR, Embeddings, Rerankers, VLM) * MLOps и Data Management: Организация и автоматизация процесса разметки данных (от сбора до контроля качества краудсорсинга) * развитие автономных пайплайнов улучшения качества моделей с использованием LLM-as-a-Judge * Engineering: релиз новых моделей и сервисов в продуктовые среды. Требования * Глубокое понимание LLM: опыт работы с большими языковыми моделями, Prompt Engineering, Fine-tuning LLM/VLM * инженерная культура: уверенное владение Python 3, знание ООП, принципов SOLID. Хорошее знание алгоритмов и структур данных. * LLM Stack: опыт работы с LangChain, LlamaIndex или другими фреймворками для разработки агентов и мультиагентных систем (MAS) * Vibe Coding: умение автоматизировать собственные рутинные процессы с помощью AI-инструментов * Mindset: желание постоянно изучать новые SOTA-подходы, модели и технологии. **Будет плюсом** * Активный профиль на GitHub с качественным кодом * достижения (медали) на Kaggle * участие в Open-Source проектах, связанных с LLM/NLP. Условия * комфортный современный офис - м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовой бонус * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.

Location: Brussels, Belgium We currently have a vacancy for an Operations Engineer fluent in English, to offer his/her services as an expert who will be based in Brussels, Belgium. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team. Your tasks: Architect and implement secure, interoperable solutions using standard frameworks and design patterns, integrating application and infrastructure to achieve scalability and efficiency; Develop robust, vendor-agnostic data platforms for AI and machine learning workloads, optimising multi-cloud environments for performance and flexibility. Design of structured MLOps pipelines automating and streamlining the models’ lifecycle, from development to serving; Design security architectures that protect infrastructure and applications, aligning with risk management strategies and regulatory data protection and security standards; Continuously assess and optimise system performance and scalability using advanced metrics and predictive analytics; Collaborate with cross-functional teams, including AI developers, business analysts, and IT operations, to ensure architecture aligns with business objectives and technological capabilities; Establish CI/CD pipelines to support rapid application development and deployment in dynamic environments, utilising infrastructure-as-code and configuration management tools; Ensure seamless system integration and cross-platform compatibility through strategic API design, interoperability testing, and continuous benchmarking. Requirements University degree in IT combined with relevant IT professional experience of at least 10 years; Expertise in containerisation and orchestration using Docker and Kubernetes for scalable application deployment; Expertise in network architecture design, particularly integrating distributed systems with hybrid cloud solutions and including management of network policies at cluster level; Significant experience with managing and optimising data-intensive distributed systems for processing, querying and storing; Comprehensive experience with relational and non-relational databases, optimising them for high-volume transaction processing (e.g., Oracle, PostgreSQL, OpenSearch, MongoDB) Proficiency with advanced monitoring tools like Prometheus and Grafana to enhance infrastructure monitoring and real-time alerting; Experience with advanced load balancing solutions and caching technologies (e.g. Redis) to support high-traffic applications; Knowledge of security and vulnerability scanning tools (e.g., OWASP, SonarQube), implementing secure coding practices including robust encryption and identity management; Profound knowledge of version control systems like Git and integration platforms such as Jenkins, GitLab CI; Proficiency in distributed streaming and message queue technologies such as Kafka and RabbitMQ to efficiently manage data flows and support scalable data processing architectures; Proficiency in using infrastructure-as-code like Terraform and AWS CloudFormation; Good knowledge of the GitOps framework and tools that follow its prescription to manage deployments and achieve the desired application state (e.g., ArgoCD); Familiarity with configuration management tools like Ansible for comprehensive system administration; Familiarity with AI-powered code assistants (e.g., Amazon Kiro, GitHub Copilot) for accelerating coding processes and enhancing developer productivity; Excellent command of the English language. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference: ( 158836/10/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. You may also consider all our other open vacancies by visiting the career section of our web site ( www.eurodyn.com) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS ( www.eurodyn.com ) is a leading Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 300 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in www.eurodyn.com/privacy. By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

Location: Москва Мы рады пригласить Эксперта-методолога AI Governance в команду Sber AI. Мы развиваем AI, занимаемся созданием инфраструктуры для AI, управляем процессом и настраиваем роли, обеспечивающие разработку и внедрения AI-решений в Банке. Наша команда отвечает за аналитику в области AI, внедрение AI Governance стандартов, разработку методологии и дизайн процессов, мы также проводим различные аналитические исследования по развитию AI рынков и технологий. Мы верим, что именно люди создают атмосферу и являются драйверами инноваций. Если тебе интересно развиваться в области AI, присоединяйся к нам. Обязанности * определение процессов и систем управления процессами разработки и внедрения AI-решений (Ml-моделей, AI-агентов) * сбор, анализ и агрегация требований по CDS-вертикали к инструментам и процессам, обеспечивающим разработку ML-моделей и AI-агентов в Банке; * создание и внедрение системы дэшбордов по системе управления разработкой и внедрением AI-решений в Банке * проектирование логики сбора и визуализации "цифровых следов" работы команд D-people при разработке AI-решений (ML-моделей и AI-агентов) * обеспечение поддержки функционирования проектов на всех этапах жизненного цикла, контроль выполнения сроков и объемов работ, подготовка статус-отчетов * анализ ключевых международных AI-решений, в том числе с детальным пониманием используемых технологий, преимуществ и недостатков данных технологий * разработка и согласование внутренних нормативных документов в соответствии с требованиями Банка. Требования * высшее образование в сфере информационных технологий, экономики или менеджмента * знание методик разработки моделей машинного обучения; * знание практик MlOps /технологий, используемых для разработки и внедрения AI-решений * понимание принципов работы LLM, ML-инструментов и их влияния на пользовательский опыт * знание основ создания и логики работы AI-агентов * аналитическое мышление: способность быстро анализировать информацию, выявлять закономерности и тенденции, формировать обоснованные выводы и рекомендации * грамотный русский язык, развитые навыки устной и письменной коммуникации, включая ведение деловой переписки * отличное владение визуальными средствами коммуникации, инструментов визуализации данных, подготовка и проведение презентаций * развитые навыки формирования отчетов и презентаций * уровень английского языка Intermediate и выше. **Будет преимуществом:** * опыт создания прототипов дэшбордов в Qlik (или аналогах) для быстрой валидации гипотез перед передачей в команду BI-разработки * опыт работы в стратегическом консалтинге * инструментальное владение AI для анализа, исследования, генерации и автоматизации рутинных процессов. Условия * комфортный современный офис на Кутузовском, 32 * корпоративный спортзал и зоны отдыха * уникальная система обучения Сбера для профессионального и карьерного развития, семинары, тренинги, конференции * программа адаптации и помощь руководителя на старте * ДМС, страхование от несчастных случаев, социальные гарантии * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * крпоративная пенсионная программа.

Mistral is looking for a Research Engineer GPU Performance to optimize generative AI model training and inference on GPUs.

Mistral is looking for an Applied AI Technical Lead Forward Deployed AI Engineer to lead enterprise AI solution delivery and customer deployments.

Location: Athens Workplace: Remote About the company: KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe. About the role We are looking for an ML Engineer to improve automatic speech recognition (ASR) for Sophea Meet. You will work with real meeting audio and own the improvement loop from data and model experiments through evaluation and production performance. The initial language focus is English. Additional languages, starting with Greek, will be prioritized with Product based on usage and product needs. What you will do - Train, fine-tune, adapt, and evaluate speech recognition models based on measured product needs. - Build representative benchmarks and regression tests for real meeting audio. - Prepare speech datasets and investigate difficult cases, including noise, overlapping speakers, long sessions, and specialized terminology. - Use error analysis to decide which model, data, or pipeline changes will improve transcription quality. - Improve inference across accuracy, latency, throughput, reliability, and cost. - Deploy and monitor model versions with Engineering, while working with Product to set quality goals and prioritize improvements. What you will need - 3+ years of relevant ML or research engineering experience, with clear technical ownership and measurable results. - Strong hands-on ASR or speech ML experience, including a speech recognition system you shipped or materially improved. - Experience training, fine-tuning, or adapting deep learning models using real-world audio data. - Strong evaluation skills, including WER/CER, benchmark design, error analysis, and regression testing. - Strong Python, hands-on experience with PyTorch, JAX, TensorFlow, or a similar framework, and solid software engineering skills. - Experience deploying, monitoring, and maintaining production ML systems. Nice to have - Multilingual ASR, accent robustness, domain adaptation, or diarization. - Streaming speech recognition and low-latency inference. - MLOps, evaluation, or data pipelines for speech systems. - Experience with meeting transcription, voice agents, or enterprise speech products. What is there for you - Compensation: Competitive package aligned with talent benchmarks. - Impact: Hands-on work shaping AI capabilities for Kiefer Tech’s products and real-world applications. - AI-native environment: Real challenges across model development, evaluation, and production AI systems. - Culture: Engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products.

Location: Serbia; Spain Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another. Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world. We bring together a team of like-minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world. We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025). We are looking for Machine Learning Engineer. Your main tasks will be: Set the ML direction: choose which strategic bets to make and tie each one to clear business needs. Drive LLM post-training and model adaptation end to end, from dataset construction to fine-tuning and preference optimization. Design and build agent harnesses and tool-using LLM systems. Shape multi-agent development workflows that make the team faster and more effective. Build evaluation frameworks and LLM-as-a-judge systems that reliably predict real-world performance. Improve dialogue quality across memory, emotional intelligence, persona consistency, safety and anti-loop behavior. Ship production systems that directly shape user experience, retention and monetization. We expect from you: Python expert level: clean code, typing, async, multiprocessing, profiling, debugging, notebooks + production code.Trainsformers. Training and fine-tuning LLMs. SFT, LoRA/QLoRA, PEFT. Preference optimization: DPO / ORPO / SimPO / CPO / GRPO or willingness to quickly go deep. Building datasets for LLM training: cleaning, filtering, deduplication, preference pairs, synthetic data, hard negative mining. LLM evaluation: offline evals, pairwise evals, LLM judges, human annotation. Agent harness design: tool calling, function calling, structured outputs, retries, routing, state management, memory/context, guardrails. Production LLM integration: APIs, streaming, batching, fallbacks, cost/latency trade-offs. Observability for agents: traces, tool-call logs, transcript analysis, failure clustering. Strong understanding of transformer architecture and modern LLM behavior. Accuracy with dtype/device/batching: fp32/fp16/bf16, quantization, CUDA memory, avoiding dtype mismatch bugs. Git, Docker, Linux, basic MLOps. Fluent Russian, ready to work in CET (±2) hours. Nice to have: experience beyond text (computer vision, image generation, multimodal), long-running conversations and character consistency, vLLM / TGI / SGLang, DeepSpeed / FSDP / Accelerate, quantization, safety classifiers. What do we offer: REMOTE OPPORTUNITY to work full-time; The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment; Vacation 28 calendar days per year; 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave; Bonuses up to $5000 for recommending successful applicants for positions in the company; 50% payment for professional training, international conferences, and meetings; Corporate discount for English lessons; ​ Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); ​ Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years; Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now!