Remote AI/ML Engineer - Build Production Models & Pipelines

US Health Partners, LLC; United Kingdom; Remote; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Flexible work environment

Healthcare

Equity in the company

Time off

Home office setup ($500)

Global gatherings

Job summary

ClickHouse’s AI/ML Engineering team builds AI and ML products end-to-end, including the Agentic Data Stack, AI Functions, and in-Console copilot. We seek engineers to design, build, and operate features across the full stack for ClickHouse Cloud, integrating with external AI services and ensuring robust production deployment.

You will own ML pipelines, collaborate across teams, and work in a remote-friendly, globally distributed environment with strong ownership and impact on AI workloads.

Qualifications

• 5+ years of software engineering experience in production environments.
• Exposure to working directly with AI/ML technologies.
• Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases.

Responsibilities

• Design and implement AI-powered features across the full stack within the ClickHouse Cloud platform.
• Create robust, scalable APIs connecting database capabilities with AI/ML inference systems.
• Integrate and maintain ecosystem integrations with major AI/ML tools and frameworks.
• Deploy models into production with monitoring, versioning, and observability.
• Participate in daytime oncall rotations.
• Own the ML pipeline end-to-end (data, training, evaluation) and iterate based on state-of-the-art insights.

Skills

Software engineering

AI/ML experience

Python

PyTorch

Ray

Slurm

Production deployment

Tools

PyTorch

Ray

Slurm

Job description

ClickHouse’s AI/ML Engineering team builds AI and ML products end-to-end, including the Agentic Data Stack, AI Functions, and in-Console copilot. We seek engineers to design, build, and operate features across the full stack for ClickHouse Cloud, integrating with external AI services and ensuring robust production deployment.

You will own ML pipelines, collaborate across teams, and work in a remote-friendly, globally distributed environment with strong ownership and impact on AI workloads.