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 @ 1
GCP @ 3
JavaScript @ 7
Machine Learning
Observability
Python @ 4
React @ 7
TypeScript @ 4
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, AI/ML partnerships, and shared components that enable other ClickHouse teams to ship AI products.
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 and 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.
- Backend development experience with TypeScript or Python, focused on API design and service architecture.
- Strong ownership and the ability to drive features from concept through production with minimal supervision.
- Ability to collaborate effectively and communicate technical concepts 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 services related to AI/ML deployment.
- Understanding of database systems and data processing pipelines; ClickHouse experience is a significant plus.
- Experience building data-oriented interfaces and visualizations.
Compensation
The typical starting salary for this role in the United States is $141,000–$195,000 USD. In US premium markets, such as the San Francisco Bay Area and New York City Metro Area, the typical starting salary range is $158,000–$232,000 USD. Actual compensation depends on factors including education, qualifications, certifications, experience, skills, location, performance, and business needs.
Benefits
- Flexible work environment at a globally distributed, remote-friendly company.
- Employer healthcare contributions.
- Stock options for new team members.
- Flexible time off in the United States and generous entitlement in other countries.
- $500 home office setup for remote employees.
- Opportunities to participate in company-wide offsites and global gatherings.
- Equal employment opportunities and a commitment to a workplace free from discrimination and harassment.
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