Machine Learning Engineer
At a glance
Mid-level Machine Learning Engineering role at ClickHouse. United Kingdom · full-time · no salary stated · we estimate £60,000–£97,524 across the United Kingdom.
ClickHouse has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI features across backend inference services and frontend experiences in ClickHouse Cloud
- Design APIs that link ClickHouse database capabilities with AI inference systems and other services
- Connect ClickHouse with AI and ML frameworks, tools, and ecosystem standards
- Deploy models with monitoring, version control, observability, and evaluation in place
- Run ML pipelines from data through training and evaluation, and join daytime on-call rotations
What you bring
- At least five years building and operating software in production environments
- Hands-on experience deploying AI or ML models, including inference APIs and vector databases
- Applied ML work in Python, experience with compute clusters, and well-designed experiments
- You can take features from early concept to production with little supervision
Who this fits
This mid-level role suits a software engineer with practical ML experience who can own delivery across the stack. You’ll work in a collaborative team and take part in its daytime on-call rotation. The role is remote-friendly, and the posting describes ClickHouse as globally distributed.
From the employer
Recognised on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We’re on a mission to transform how companies use data. Come be a part of our journey!
About the team
The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists.
What you will do
Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform.
API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services.
Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools.
Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation.
Oncall: Participate in the daytime oncall rotation along with the rest of the team.
ML Engineering: Own the ML pipeline end to end (data, training, evaluation), and fine-tune or train custom models when off-the-shelf ones fall short. Track the state of the art closely enough to apply what genuinely improves our products.
What you will bring along
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
A high level of ownership and can drive features from concept to production with minimal supervision
Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders
Applied ML experience in Python (Jupyter, PyTorch, common ML libraries), hands-on with compute clusters (Ray, Slurm), and designs trustworthy experiments to drive architectural decisions
Nice to have
Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment
Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus
Experience with embedding-based systems (retrieval, ranking, recommenders) and the representation-learning ideas underneath them
Perks
Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
Healthcare - Employer contributions towards your healthcare.
Equity in the company - Every new team member who joins our company receives stock options.
Time off - Flexible time off in the US, generous entitlement in other countries.
A USD$500 Home office setup if you’re a remote employee.
Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
Culture - We All Shape It
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here. Check out our blog posts or follow us on LinkedIn to find out more about what’s happening at ClickHouse.
Equal Opportunity & Privacy
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here for our Privacy Statement.