Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 4
AWS @ 3
Azure @ 3
ClickHouse @ 4
GCP @ 3
JavaScript @ 7
Machine Learning
Observability
React @ 7
TypeScript @ 7
Vector Databases @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end, including the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and AI/ML partnerships. The team is seeking experienced software engineers to design, build, and operate products that make ClickHouse the platform of choice for agents and data scientists.
Responsibilities
- Design and implement AI-powered features across the full stack, from backend inference services to frontend interfaces within the ClickHouse Cloud platform.
- Create robust, scalable APIs connecting ClickHouse database capabilities with modern AI/ML inference systems and internal or external AI services.
- Implement and maintain integrations with the broader AI/ML ecosystem and relevant standards.
- Integrate models into production systems with monitoring, versioning, observability, and evaluation.
- Participate in the daytime on-call rotation.
- Build responsive, intuitive user interfaces that make complex AI functionality accessible to users with varying technical backgrounds.
Requirements
- 5+ years of software engineering experience in production environments.
- Exposure to AI/ML technologies.
- High ownership and the ability to drive features from concept to production with minimal supervision.
- Ability to work collaboratively and communicate technical concepts effectively to diverse stakeholders.
- Strong frontend skills with TypeScript, JavaScript, and React.
Nice to Have
- Experience integrating and deploying AI/ML models in production systems, including inference APIs and vector databases.
- Familiarity with AWS, Azure, or GCP, particularly AI/ML deployment services.
- Understanding of database systems and data processing pipelines; ClickHouse experience is a significant plus.
- Experience building data-oriented interfaces and visualizations.
Benefits
- Flexible, remote-friendly work environment at a globally distributed company operating in more than 25 countries.
- Employer healthcare contributions.
- Stock options for new team members.
- Flexible time off in the United States and generous entitlement in other countries.
- USD 500 home office setup allowance for remote employees.
- Opportunities to participate in company-wide offsites and global gatherings.
Additional Information
ClickHouse provides equal employment opportunities and prohibits discrimination and harassment based on legally protected characteristics. Applicants can review the company's privacy statement through the ClickHouse applicant privacy notice.
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