Machine Learning Engineer (AI/ML)
$150k - $238k • Remote • New York • FullTime
Posted 10d ago
Job Location
New York
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
ClickHouse is a rapidly growing cloud company specializing in real-time analytics, data warehousing, observability, and AI workloads. The AI/ML Engineering team is responsible for building and operating the company's AI and machine learning products end-to-end, including the Agentic Data Stack, AI Functions, and in-console copilot. We are seeking experienced software engineers to design, build, and operate these cutting-edge AI products, making 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.
- Create robust, scalable APIs connecting database capabilities with AI/ML inference systems and external/internal AI services.
- Integrate and maintain integrations with the broader AI/ML ecosystem and standards.
- Integrate models into production systems with proper monitoring, versioning, observability, and evaluation.
- Participate in the daytime oncall rotation.
- Own the ML pipeline end-to-end (data, training, evaluation), and fine-tune or train custom models.
- Track the state of the art to apply genuine product improvements.
Requirements
- 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 inference APIs and vector databases.
- High level of ownership and ability to drive features from concept to production with minimal supervision.
- Ability to thrive in collaborative environments and effectively communicate technical concepts.
- Applied ML experience in Python (Jupyter, PyTorch, common ML libraries).
- Hands-on experience with compute clusters (Ray, Slurm).
- Experience designing trustworthy experiments to drive architectural decisions.
- Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly AI/ML deployment services.
- Understanding of database systems and data processing pipelines.
- Experience with embedding-based systems (retrieval, ranking, recommenders) and representation learning.
Benefits
- Flexible work environment (globally distributed and remote-friendly).
- Employer contributions towards healthcare.
- Equity in the company (stock options).
- Flexible time off (US) / generous entitlement (other countries).
- USD$500 Home office setup for remote employees.
- Global Gatherings (company-wide offsites).