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Build and maintain the FinFAST platform’s full-stack features, integrating LLM APIs for an AI research assistant and creating interactive dashboards to visualize economic data.
Build and run multi-cloud infrastructure for AI platforms using Terraform, Kubernetes, and CI/CD pipelines to ensure scalable, secure, and cost-efficient services.
Build and deploy generative AI and ML applications using embeddings and vector databases to improve healthcare analytics and solutions.
Build and deploy generative AI and ML models, focusing on embeddings and vector databases, to improve healthcare solutions and processes.
Leads architecture and engineering for an AI data engine that accelerates ML dataset generation and warehouse operations for autonomous-vehicle models, using cloud infrastructure and agentic AI workflows.
Senior Data Engineer builds and scales Python-based data pipelines (Pandas, PySpark, dbt, Airflow) on Snowflake/BigQuery, ensuring reliability and performance for analytics and AI workloads.
Build and deploy computer vision and generative AI models for retail applications like visual search, personalized recommendations, and fraud detection using PyTorch, diffusion models, and multimodal systems.
Leads a tiger team to modernize AI/ML platforms, integrating LLMs (RAG, embeddings) and automating data pipelines for customer identity resolution, while mentoring teams on next-gen AI development and .NET/React-based infrastructure.
Lead enterprise GenAI strategy, architect scalable AI systems, and advise C-suite on tech stacks, trade-offs, and ROI for large client engagements.
Обязанности: Разрабатывать системы анализа здоровья: наше ключевое направление AI, который помогает пользователю понять своё состояние и вовремя дойти до врача; Внедрять AI-фичи в продукт и в компанию: интеграция LLM…
Design and deliver enterprise-scale AI/ML and generative AI systems, including RAG, agents, and Snowflake Cortex integrations, while leading architecture reviews and client engagements.
Build and deploy ML/AI models end-to-end, from data exploration to production, using Python, PyTorch/TensorFlow, and cloud platforms like AWS/GCP/Azure.
Департамент информационных технологий Москвы создает и развивает цифровые проекты, которые делают столицу комфортнее, а жизнь горожан — удобнее и мобильнее. Для системы управления столицей технологии — это незаменимый…
Lead AI/ML engineering projects, building and deploying LLM applications with RAG pipelines and MLOps tooling.
Builds and optimizes ETL pipelines, vector databases, and LLMOps for AI services using Python/Java/Scala, focusing on RAG/LLM workflows and multimodal data.
Build AI-powered applications using LLMs, RAG, and agents, and develop scalable backend services with Python, .NET, and React for Playtech’s gaming platforms.
Build and deploy autonomous AI agents and RAG pipelines to automate safety training analytics and compliance workflows, integrating with enterprise systems like CRM and LMS.
Design and lead the architecture of AI-native applications, including agent systems, LLM infrastructure, and scalable data pipelines, while ensuring security and compliance for production-grade systems.
Build AI-driven features and autonomous agents for Cisco’s Partner Hub, integrating LLMs and agentic frameworks to automate workflows and deliver predictive insights for partners.
Design and build AI-powered systems that automate software delivery workflows, integrating agentic AI into R&D, product management, and DevOps toolchains.
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