machine learning engineer for AI workloads

ClickHouse develops a platform for real-time analytics, data warehousing, observability, and AI workloads. Its AI/ML Engineering team builds and operates AI and machine learning products, including the Agentic Data Stack, AI Functions, chDB, an in-Console copilot, and AI/ML partnerships.

• Design and implement AI-powered features across the full stack, from backend inference services to frontend interfaces within the ClickHouse Cloud platform
• Create scalable APIs connecting ClickHouse database capabilities with AI/ML inference systems and internal and external AI services
• Implement and maintain integrations with the broader AI/ML ecosystem, standards, frameworks, and tools
• Integrate models into production systems with monitoring, versioning, observability, and evaluation
• Participate in the daytime on-call rotation
• Own the end-to-end ML pipeline, including data, training, and evaluation
• Fine-tune or train custom models when off-the-shelf models fall short
• Track advances in the field and apply those that improve the products

• 5+ Years of software engineering experience in production environments
• Experience working directly with AI/ML technologies
• Experience integrating and deploying AI/ML models in production systems, including inference APIs and vector databases
• Ability to drive features from concept to production with minimal supervision
• Ability to work collaboratively and communicate technical concepts to diverse stakeholders
• Applied ML experience in Python, including Jupyter, PyTorch, and common ML libraries
• Hands-on experience with compute clusters such as Ray and Slurm
• Ability to design trustworthy experiments to inform architectural decisions
• Будет плюсом: familiarity with AWS, Azure, or GCP, especially AI/ML deployment services; understanding of database systems and data processing pipelines; ClickHouse experience; experience with embedding-based systems, including retrieval, ranking, recommenders, and underlying representation-learning concepts

• Employer contributions toward healthcare
• Stock options for every new team member
• Flexible time off in the US and generous time off in other countries
• USD$500 home office setup allowance for remote employees
• Opportunities to attend company-wide offsites
• The company operates in over 25 countries