Вакансии

Location: Warszawa, Poland; Almaty, Kazakhstan; Prague, Czechia; Tallinn, Estonia; Tbilisi, Georgia; Budapest, Hungary; Rīga, Latvia; Vilnius, Lithuania; Lisboa, Portugal; Bucharest, Romania; Madrid, Spain Workplace: fully Customer Description: The customer is a global mobility and urban services platform providing transportation and other on-demand services through a digital marketplace. Project Description: The work spans deep learning model development, large-scale geospatial data pipelines, and low-latency production serving. The candidate will measure the impact through offline evaluation metrics and the results of online experiments Project Phase: ongoing Soft Skills: • Ability to influence teammates and cross-functional stakeholders effectively. • Curious and improvement-oriented mindset with a willingness to challenge existing approaches. • Excellent ability to communicate complex technical findings in a clear and concise manner. Hard Skills / Must Have: • 5+ years of machine learning engineering experience building and deploying deep learning models in production. • Experience building regression, forecasting, or other supervised machine learning systems for production prediction tasks. • Expert-level proficiency in Python and its core data science libraries (e.g., PySpark, Pandas, NumPy, Scikit-learn, PyTorch; gradient-boosting libraries such as CatBoost/XGBoost/LightGBM). • SQL. • Ability to design an ML system from scratch, including data analysis and processing. • Experience translating business goals into ML problems with appropriate metrics and non-functional requirements. • Experience designing and evaluating ML experiments. • Experience with MLOps tools. • Experience working with large-scale geospatial and behavioral datasets. • Experience deploying models to production on ML serving infrastructure and optimizing for latency, and awareness of concept drift and how to detect and manage it. • Comfort working with large-scale geospatial and behavioral data (e.g., GPS traces, H3 spatial indexing) Hard Skills / Nice to Have (Optional): • Academic background in Computer Science, Mathematics, or a related discipline. • Experience with travel time prediction, traffic estimation, or routing quality. • Experience with open-source routing engines. • Knowledge of map matching, speed profiles, road graph tiles, and historical traffic. • Experience with mapping, location, or geospatial products. • Experience building products for developing markets. • Experience with cloud data and machine learning platforms. Responsibilities and Tasks: • Design and build machine learning models to improve routing and travel time prediction. • Develop traffic estimation models using large-scale GPS data. • Implement map-matching solutions for noisy GPS data. • Improve travel time calculation, smoothing, and rerouting logic. • Translate routing objectives into machine learning objectives and evaluation metrics. • Lead offline and online model evaluation activities. • Collaborate with backend engineers to deploy low-latency production models. • Partner with product and operations teams to define new features and requirements. • Own the production ML lifecycle, including serving, monitoring, drift detection, and retraining pipelines. 🧪 Technology Stack: }Python, SQL, PySpark, Pandas, NumPy, Scikit-learn, PyTorch, XGBoost, LightGBM, CatBoost, MLOps, ML Lifecycle Management, Production ML Systems, ML Infrastructure, Geospatial Analytics, GPS Data, H3 Spatial Indexing 📝 Additional notes: The work will be carried out either on client's equipment or via a virtual workstation. Requires fluent Russian , as part of the team communication is conducted in Russian

Location: Helsinki; Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry. The Voodoo Ad-Network is an autonomous product group of around 60 highly driven professionals with an ambitious mission: building top-tier ad network services. Our primary goal is to leverage Voodoo's massive first-party data ecosystem to optimize and scale monetization. We are in a rapid growth phase, expanding into new ventures such as opening to external inventory, penetrating the external advertiser market, and driving social network monetization following our recent acquisition of BeReal. To support this incredible trajectory and promising early results, we are scaling our team. The Models team is a core element of the targeting performance. It leverages machine learning and a strong business understanding to directly impact the product's financial performance. It's composed of mostly senior Data Analysts, Analytics Engineers, Data Engineers and Data Scientists/ML Engineers that iterate together on finding and building the next performing iteration. This role can be either Paris or Helsinki based and done in a hybrid setup. ROLE We're looking for a Senior ML Engineer to join our Models team. You will be joining a dedicated squad of Data Engineers, Data Scientists, and ML Engineers focused on building and maintaining the ML training infrastructure that powers our ad-targeting models from data preprocessing through model deployment to production monitoring. In this role, you will be leading the following topics: - Architectural Ownership: Take end-to-end ownership of highly visible projects from ideation to production release. This includes feature scoping, timeline estimation, architecture design, and benchmarking new technologies. - Pipeline Engineering: Build and maintain quality data and ML pipelines to align with ever-evolving business and machine learning needs. Optimize training pipelines for performance, memory efficiency, and cost (e.g. spot instance strategies, efficient data loading, preprocessed artifact reuse). - Data Scientists Enablement: Enable Data Scientists to iterate faster by providing reusable, well-tested pipeline components (transformers, dataloaders, training utilities) and reviewing their contributions to shared code. Extend dataset capabilities: integrating new data sources, scaling feature windows, and increasing training data volumes without breaking pipeline constraints. - Deep Learning Development: Contribute to deep learning development: GPU workload orchestration, custom PyTorch training loops, and model architecture support. - ML Lifecycle & Reproducibility: Maintain reproducibility and consistency across the ML lifecycle: versioned configs, experiment tracking, and online-offline consistency tooling. - Scalability & Reliability: Collaborate with infrastructure teams on scalability — node pools, resource monitoring, CI/CD migrations. Participate in weekly rotation to triage and resolve alerts from Airflow, dbt, and related systems. - Agile Collaboration: Thrive in a fast-paced agile environment with rapid decision-making processes. You will collaborate daily with back-end developers, data scientists, infrastructure engineers, and product managers. - Mentorship & Team Culture: You will actively contribute to our engineering culture, share knowledge, and ensure every team member feels comfortable, supported, and empowered to grow in their role. PROFILE We are looking for a Senior ML Engineer who deeply understands both the ML training lifecycle and the specific challenges of putting machine learning models into production at scale. - 5+ years minimum of experience as an ML Engineer or a similar role - End-to-End ML Ownership: Problem framing, baselines, experimentation, deployment, and iteration - Python Proficiency: Extensive knowledge for ML pipeline code: preprocessing, training/evaluation workflows, experiment utilities, and reproducible configs - Training Mechanics: Comfortable implementing training mechanics where needed (custom steps/metrics, dataloading patterns, performance-conscious preprocessing), not only notebook-level prototyping - ML Frameworks: Practical experience training and evaluating models with scikit-learn, LightGBM, PyTorch for deep learning - Performance Optimization: Experience optimizing memory usage during data preprocessing and model training - Experiment Management: Hyperparameter tuning, experiment tracking, and reproducible training (configs, seeds, versioning) - Cloud & Infrastructure: Experience with Amazon Web Services. Familiarity with scalability, reliability, and security topics - ML Production Awareness: Understanding of the challenges involved in running ML models in production (familiar with topics such as feature store, training-serving skew, etc.) - Model Serving: Experience with model serving infrastructure (real-time or batch inference, latency/throughput optimization) is a plus - Excellent communication skills in English OUR STACK Python · Scikit-learn · LightGBM · PyTorch · DBT · Spark · MLflow · Prometheus · Terraform · Airflow · Kubernetes · Amazon Web Services BENEFITS - Excellent benefits that will depend on the country you're based in

Обязанности: • разработка и совершенствование End-to-End ML-пайплайнов • разработка продакшен-пайплайнов обработки данных • работа с огромными объёмами данных Сбера (петабайты) на PySpark, исследование подходов применения их в моделях • писать эффективный и масштабируемый код для тренировки и инференса моделей на PyTorch, проводить эксперименты на GPU-кластере • performance оптимизации кода по обработке больших массивов данных или онлайн сервисов рекомендаций с высокой нагрузкой • менторинг младших членов команды, обмен знаниями и экспертизой. Требования: • математический бэкграунд • хорошее знание Python и ключевых фреймворков для работы с данными (PySpark, PyArrow, Pandas) • опыт написания качественного production кода • опыт написания промышленных пайплайнов обработки данных, содержащих множество шагов, зависимостей и сложную логику • опыт использования Airflow (или другого industry-standard оркестраторов пайплайнов, т.к. Luigi, Dagster и т.д.) • хорошее понимание баз данных SQL / NoSQL • навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом • опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки. Условия: • комфортный современный офис рядом с м. Кутузовская (опционально) • возможность выбрать удобный график – офис/гибрид/удаленка (опционально) • ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) • 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.

Location: Remote or Mississauga Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary This team will serve as the product owner for the machine learning platform capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support traditional machine learning (ML) and hybrid ML/LLMsolutions. This centralized team with deep specialization will closely integrate with key horizontal partners to ensure delivery of safe, scalable, and high-impact AI products. Job Summary The Principal AI Machine Learning Platform Engineer will set the technical vision and strategy for the machine learning platform that powers ML and generative AI development across PointClickCare, partnering with Product and Engineering leadership to align that direction with product and business goals. As the technical authority for the ML platform, the Principal Engineer will define the reference architectures, standards, and roadmap for the pipelines, tooling, and infrastructure used for model training, deployment, serving, and monitoring, and will provide technical leadership and mentorship to raise the engineering bar for ML systems company-wide. Key Responsibilities Partner with product and engineering leadership to translate business and product objectives into a multi-quarter technical strategy and roadmap for the ML platform. Define the reference architectures and standards for scalable data and ML pipelines spanning model training, evaluation, deployment, and serving that engineering teams across the organization build upon. Set the direction and best practices for MLOps across the company — including CI/CD for models, model registry, feature stores, and experiment tracking — and drive build-vs-buy decisions for core platform components. Establish the practices and architecture for reliability, observability, and performance of ML systems in production, including monitoring, alerting, and automated remediation. Establish the security architecture for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring, and ensure adoption across teams. Define secure, cost-efficient integration and infrastructure patterns for connecting the platform with existing systems, APIs, and data sources at scale. Provide technical leadership and mentorship across engineering teams, guiding senior engineers and influencing the org-wide technical roadmap for ML infrastructure. Qualifications & Skills Expert level in Python and Java with strong software engineering fundamentals. Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents. Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes). Demonstrated track record of setting technical direction and driving org-wide technical initiatives across multiple teams. Preferred Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field. Sufficient familiarity with Azure Machine Learning components, Databricks processing and serverless environments, and ML Frameworks to support strategic decision making Demonstrable history of leading and sustaining build out of critical cross-team systems Experience implementing security at scale including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring. Experience optimizing large model training and inference (including LLM serving) for performance and cost. #LI-AV1 #LI-hybrid PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information.

Location: Remote, USA Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary This team will serve as the product owner for the machine learning platform capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support traditional machine learning (ML) and hybrid ML/LLMsolutions. This centralized team with deep specialization will closely integrate with key horizontal partners to ensure delivery of safe, scalable, and high-impact AI products. Job Summary The Principal AI Machine Learning Platform Engineer will set the technical vision and strategy for the machine learning platform that powers ML and generative AI development across PointClickCare, partnering with Product and Engineering leadership to align that direction with product and business goals. As the technical authority for the ML platform, the Principal Engineer will define the reference architectures, standards, and roadmap for the pipelines, tooling, and infrastructure used for model training, deployment, serving, and monitoring, and will provide technical leadership and mentorship to raise the engineering bar for ML systems company-wide. Key Responsibilities Partner with product and engineering leadership to translate business and product objectives into a multi-quarter technical strategy and roadmap for the ML platform. Define the reference architectures and standards for scalable data and ML pipelines spanning model training, evaluation, deployment, and serving that engineering teams across the organization build upon. Set the direction and best practices for MLOps across the company — including CI/CD for models, model registry, feature stores, and experiment tracking — and drive build-vs-buy decisions for core platform components. Establish the practices and architecture for reliability, observability, and performance of ML systems in production, including monitoring, alerting, and automated remediation. Establish the security architecture for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring, and ensure adoption across teams. Define secure, cost-efficient integration and infrastructure patterns for connecting the platform with existing systems, APIs, and data sources at scale. Provide technical leadership and mentorship across engineering teams, guiding senior engineers and influencing the org-wide technical roadmap for ML infrastructure. Qualifications & Skills Expert level in Python and Java with strong software engineering fundamentals. Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents. Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes). Demonstrated track record of setting technical direction and driving org-wide technical initiatives across multiple teams. Preferred Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field. Sufficient familiarity with Azure Machine Learning components, Databricks processing and serverless environments, and ML Frameworks to support strategic decision making Demonstrable history of leading and sustaining build out of critical cross-team systems Experience implementing security at scale including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring. Experience optimizing large model training and inference (including LLM serving) for performance and cost. #LI-AV1 #LI-remote PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The US base salary range for this position is $158,000-$198, 000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.

Кого ищем: — Сильного ML-инженера с опытом в трейдинге, который уже имеет опыт разработки прибыльных ML-моделей и торговых стратегий. — Способного самостоятельно генерировать и валидировать торговые идеи, строить исследовательские пайплайны и доводить стратегии до продакшн-состояния. Чем заниматься: — Разрабатывать и улучшать торговые стратегии. — Строить ML и количественные модели для прогнозирования и генерации сигналов. — Анализировать временные ряды и рыночные данные в реальном времени. — Тестировать гипотезы и улучшать существующие стратегии. — Работать с бэктестинговой инфраструктурой. Условия: — Достойная заработная плата в долларах США или криптовалюте. — Удалённый формат работы из любой точки мира, полная занятость. — Оформление через юридическое лицо в Республике Беларусь. — Небольшая команда с минимумом бюрократии, что обеспечивает быстрое принятие решений и оперативную проверку гипотез.

Location: New York, NY or Remote About Us: EvolutionIQ’s mission is to deliver state of the art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient, so that more people impacted by injury or illness can continue their lives with dignity and stability. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row and Built In’s Best Places to work in 2025 and 2026! About You : A Senior Machine Learning Engineer who thrives on first principles problems that no one has ever worked on before. You love innovation and making an immediate impact, and are constantly driving toward launch and delivery thanks to your high degree of ownership and control. You love working on new and challenging problems, not incremental or marginal improvements, and you're supercharged by having interesting, unsolved problems continually present themselves. In this Role, You Will: Build ML models for production use Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies Suggest and implement new features to improve model performance and business logic Write and review production-quality PRs daily Translate client business problems into ML problems Build scalable machine learning models for claim time series forecasting and NLP text understanding Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets Requirements : 2+ years of experience as a Machine Learning Engineer or Data Scientist, preferably in highly scalable production environments. You have deep exposure to data science & ML tech stacks (sklearn, Keras / PyTorch, tuning frameworks), data analysis & modeling, feel at home in Python/Pandas/Jupyter, and strive for scalable technical concepts and solutions. You have excellent written and verbal communication skills and can effectively correspond between technical and non-technical audiences. You’re a team player who is solutions-oriented. Experience leveraging Claude Code and related tools is a strong plus Even Better if You Have the following: Knowledge of Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes Owned and deployed, and maintained model-serving pipelines in production Expert skills at writing clean, efficient, and easy-to-understand code with unit tests and functional design patterns Experience with advanced statistical modeling, especially probabilistic programming Ambitious, collaborative, and empathetic values A work style that is open to giving and receiving critical feedback and collaborating effectively across teams Work-life, Culture & Perks: Compensation: The base salary range is $190-225K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package. Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits. Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work. Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend. Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement. Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer. EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Чего ждём от тебя Без этого не получится: - 5+ лет в ML/DS — опыт выкатывания моделей в прод и понимание практических аспектов - Уверенный Python: ООП, типизация, тесты - Классический ML: бустинги, валидация, понимание, где нейросеть избыточна, а где достаточно градиентного бустинга - Опыт с текстовыми нейросетевыми моделями: BERT-подобные трансформеры, LLM API, промпт-инжиниринг, eval-сеты - Практический опыт MLOps: пайплайны данных, оркестрация (Airflow, Kubeflow или аналоги), трекинг экспериментов - Инфраструктурный бэкграунд: Docker, CI/CD, Kubernetes, логирование и мониторинг — понимание высоконагруженных сервисов - Умение мыслить P&L: перевод метрик моделей (F1, ROC-AUC) в конверсии и деньги, защита технических решений перед бизнесом финансовыми аргументами - Опыт менторства или лидерства и желание этим заниматься

Location: Serbia; Poland; Georgia; Cyprus; Portugal; Spain We are looking for a Senior ML Engineer / ML Lead to join the small, elite team of engineers and researchers building ML-driven trading strategies in the cryptocurrency markets. The system is currently live in production, showing strong results, and scaling rapidly. We are looking for an exceptional expert to take ownership of the product, evolve our architecture, and exponentially scale the profitability of our models. You will be working directly on real PnL. This position is designed for someone who wants to see the direct financial impact of their work, thrives in an environment of high autonomy, and is committed to writing high-performance code and building sophisticated mathematical models. Responsibilities • Develop and optimise the ML architecture for our trading strategies. • Drive the full research cycle: independently generate hypotheses, implement them into production, and monitor real-world performance/profitability. • Refine and improve existing ML models to boost effectiveness. • Identify and eliminate bottlenecks in data processing pipelines and execution strategies. Tech Stack • Python (primary language) • NumPy, numba, PyTorch / JAX Requirements • Experience in a Senior ML Engineer or ML Lead role. • Proven track record of developing profitable ML models or trading strategies. • Fundamental knowledge of mathematics, statistics, and probability theory. • Ability to operate in high-uncertainty environments: formulating your own hypotheses and validating them against data. • Experience in writing high-performance, production-ready code. Nice to Have • Experience in algorithmic trading or deep domain expertise in cryptocurrency markets. • Proficiency in C++ (specifically for reading and optimizing latency-critical code paths). • Strong academic background: competition accolades, Kaggle achievements, scientific publications, or graduation from a top-tier DS program (e.g., SHAD). • Interest in mentoring and team development. Benefits • Zero bureaucracy, high autonomy, and the chance to work alongside people who share a scientific approach and a commitment to high-quality engineering. • The opportunity to directly influence the product and see the results of your work reflected in real financial outcomes.

Обязанности: - Разрабатывать и обучать модели машинного обучения, включая генераторы кандидатов - Улучшать модели оценки стоимости автомобилей - Разрабатывать решения для антифрода и модерации контента - Подготавливать и трансформировать данные для обучения и продакшена моделей - Упаковывать модели в сервисы и внедрять их в продакшен Требования: - Опыт оркестрации ML‑пайплайнов с помощью Airflow или Luigi - Умение программировать на Python или C++ - Навыки работы с SQL и NoSQL для подготовки и трансформации данных - Умение разворачивать решения в виде микросервисов с использованием FastAPI, gRPC или Docker - Хорошие теоретические знания в области машинного обучения - Понимание устройства и принципов работы одного из ML‑фреймворков или библиотек, например CatBoost или PyTorch

Ищу в штат джун ML инженера

Задачи: — Архитектура и внедрение production-ready AI / LLM / Computer Vision систем — Декомпозиция сложных технических задач — Оптимизация стоимости и латенси production рабочих нагрузок — Сотрудничество с техническими и бизнес-командами клиентов — Разработка и обучение моделей машинного обучения — Подготовка данных и проведение аналитики — Деплой и мониторинг моделей Требования: Обязательные: — 2+ года опыта в Machine Learning / AI (Data Scientist, ML Engineer, NLP, CV, Audio Engineer) — 2+ года разработки production AI / LLM систем — Свободное владение Python, TensorFlow, PyTorch, vLLM, LangGraph, LangChain (или эквивалентные) — MLOps: оптимизация стоимости и латенси — Знакомство с agentic tooling (Claude Code, Cursor) — Опыт с LLM, NLP или Computer Vision Желательные: — Опыт с GCP (Google Cloud Platform) — Опыт в content generation — Знание оптимизации локального inference — Опыт работы с LLM и генерацией контента Приветствуется портфолио с примерами production AI систем, которые вы разрабатывали.

Ищем ML Engineer в команду рекомендаций социальной сети для геймеров Gameram. Вакансия ближе к DE/MLOps — основной фокус на подготовке и доставке рекомендательных систем до пользователя и их стабильной работе в проде. Стек: Scala, Python, Spark, Airflow, Hadoop/HDFS, Kafka, ZooKeeper, ClickHouse, Superset, Redis, PostgreSQL, AWS Обязанности: — Выводить ML-модели и рекомендательные системы в production; — Развивать и поддерживать ML-инфраструктуру; — Взаимодействовать с Data Science, продуктом и другими инженерами. Требования: — 4+ года опыта в разработке; — Уверенный Scala и/или Python; — Опыт вывода ML-моделей в production и поддержки production-систем; — Опыт работы с Big Data и распределённой обработкой данных; — Понимание ML-пайплайнов и жизненного цикла моделей; — Опыт с рекомендательными системами будет большим плюсом. Условия: — full-time, удалённо (не РФ). — Зарплата: $4,000–5,000 gross / месяц.

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

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.

Delivery Hero — сервис доставки еды, работающий в 70+ странах мира. Размер команды — 10 000+ | Компания оценивается в $8B+. В компании работает много русскоговорящих ребят. Помогают с релокацией.