ClickHouse is hiring a remote ML Engineer AI/ML!
ClickHouse, a fast-growing private cloud company known for real-time analytics and data warehousing, is hiring an ML Engineer to join its AI/ML Engineering team. The team builds and operates the company's AI products end to end, including the Agentic Data Stack, AI Functions, chDB, an in-Console copilot, and related partnerships, along with shared components other teams use to add AI to their own surfaces. This is a remote role open to candidates across the company's globally distributed footprint, focused on making ClickHouse the platform of choice for agents and data scientists. The position blends full-stack product work with hands-on machine learning engineering, and includes participation in a daytime on-call rotation.
Key responsibilities
- Design and ship AI-powered features across backend inference services and frontend interfaces in the ClickHouse Cloud platform
- Build scalable APIs linking ClickHouse's database capabilities to modern AI/ML inference systems and internal or external AI services
- Develop and maintain integrations with the wider AI/ML ecosystem, frameworks, and standards
- Put models into production with monitoring, versioning, observability, and evaluation in place
- Own the ML pipeline end to end, covering data preparation, training, and evaluation, and fine-tune or train custom models when existing ones are insufficient
- Keep current with the state of the art and apply techniques that measurably improve the product
- Take part in the daytime on-call rotation with the rest of the team
Key requirements
- 5+ years of software engineering experience in production environments
- Direct exposure to AI/ML technologies
- Experience deploying and integrating AI/ML models in production, including inference APIs and vector databases
- Strong ownership and ability to drive features from concept to production with minimal supervision
- Comfort in collaborative settings and ability to explain technical concepts to varied stakeholders
- Applied ML experience in Python (Jupyter, PyTorch, common ML libraries), hands-on work with compute clusters such as Ray or Slurm, and skill in designing trustworthy experiments to guide architecture decisions
- Nice to have: familiarity with AWS, Azure, or GCP, especially AI/ML deployment services
- Nice to have: understanding of database systems and data pipelines, with ClickHouse experience a significant plus
- Nice to have: experience with embedding-based systems such as retrieval, ranking, or recommenders and the representation-learning ideas behind them
- Seniority: Senior
- Work mode: Remote
- Key skills: Python, PyTorch, Machine Learning, ML inference APIs, Vector databases, Ray, Slurm, AWS, Azure, GCP, Database systems, Embeddings and retrieval systems, ClickHouse
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