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Build and operate Upstart's ML and simulation platform infrastructure—model training, feature engineering, inference, and marketplace simulation—using Python, Kotlin, AWS, Spark/Databricks, and MLOps tooling.
As a Senior Data Engineer, you will design, build, and optimize scalable data and ML platforms for clients in the financial and public sectors using Azure, Databricks, and Python. You will lead technical design choices, implement CI/CD workflows, and mentor team members within a hybrid work environment.
Builds, deploys, and optimizes AI/ML systems for healthcare diagnostics, focusing on scalable, compliant, and production-ready ML services with Python, PyTorch, and cloud platforms.
Build and maintain scalable MLOps infrastructure on AWS to automate ML model training, deployment, and monitoring for a B2B sales-intelligence platform.
IT компания Riverstart — аккредитованы в Минцифры, входим в реестр МТК, являемся участником Торгово-промышленной палаты РФ и Нижнего Новгорода. С 2024г разрабатываем решения в области видео-аналитики, AI и ML.…
The ML Engineer/Data Scientist develops and maintains customer-centric data models and ML features to support CRM and analytics applications. The role involves working with Python, SQL, Databricks, and MLOps tools to build scalable data products within a cloud environment.
This role involves developing and deploying computer vision and machine learning solutions for industrial inspection, specifically for engine block defect detection. The position focuses on integrating algorithms, optimizing models for Cloud and Edge environments, and building efficient inference pipelines using Python, C++, and various AI frameworks.
Мы - Команда SberAds - создаем предиктивные модели и высоконагруженные сервисы по их применению для показа рекламы в интернете. Все модели используются в real-time аукционах на показ рекламы: начиная с того, чтобы…
Lead a team of software engineers building AI/ML models and platforms for Conga’s products, including feature stores, model training, and monitoring pipelines.
Salary: £57,000 - 63,000 per year Requirements: Significant professional experience in backend development at a senior level. Strong proficiency in Python, including asynchronous programming, concurrency, and…
Salary: £75,000 - 100,000 per year Requirements: Strong Python development skills Experience with machine learning experiment tracking and model registries using MLflow, Weights & Biases, Neptune, ClearML or a similar…
UFORCE exists to make aggression unaffordable. Founded in Ukraine and headquartered in London, UFORCE is a defence-technology company with operations across Europe, the United States and Asia. UFORCE builds uncrewed…
Lead Data Scientist at SberAds building and improving predictive models across the real-time ad auction pipeline using Python, Go, Spark, Kafka, ClickHouse, and MLFlow.
Data Scientist builds ML models to assess credit, market, and fraud risks for a major Ukrainian bank, using Python, SQL, and cloud tools like SageMaker.
Привет! Это команда Возвраты ML. Мы ищем талантливого Data Scientist/ML Engineer в новую ML-команду отдела «Возвраты маркетплейса». Отдел занимается обработкой и модерацией возвратов покупателя и продавца, аннуляциями,…
Мы формируем ядро команды, которая создает с нуля экосистему интеллектуальных агентов для автоматизации бизнес-процессов. Нам нужен универсальный специалист, способный вести фичи от проектирования базы данных до…
Build and scale dunnhumby’s Enterprise AI Platform, designing production-grade AI systems including RAG, agentic workflows, and LLM-powered services using Python, LangChain, and cloud-native tools.
Imagry is seeking a Jr. DevOps / MLOps Engineer to join our R&D team and help design, build, and maintain our Machine Learning (ML), integration and deployment efforts. Responsibilities: Create and maintain MLOps…
Forward Deployed AI Architect embeds with clients to learn their workflows (e.g., insurance underwriting, healthcare revenue cycle) hands-on, then redesigns and builds production GenAI systems (LLM applications, agentic workflows) on AWS. Focuses on measurable business outcomes, evaluation-driven development, and long-term blueprint improvements.
Hands-on technical leadership role designing and delivering production-grade Generative AI and Agentic AI solutions, including LLM-powered applications, RAG pipelines, multi-agent architectures, and LLMOps using Python, agent frameworks, and cloud platforms.
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