Machine Learning Engineer (AI/ML)
New
C
ClickHouseAI/ML software
Location: New York; Secondary Locations: Detroit, Canada, Austin, Phoenix, Los Angeles, San Francisco, Dallas; Workplace: RemoteFull-TimeMiddle
Salary$150K - $238K; $150K – $238K • Offers Equity • Multiple Ranges; Premium Locations (New York, Seattle, LA): $170K – $238K • Offers Equity; US General: $150K – $215K • Offers Equity
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Job Details
- Experience
- 5+ years of software engineering experience in production environments
- Required Skills
- AWSPythonPyTorchAzure
Requirements
- Have 5+ years of software engineering experience in production environments.
- Have exposure to AI/ML technologies.
- Have experience integrating and deploying AI/ML models in production systems.
- Have experience with inference APIs and vector databases.
- Have applied machine learning experience in Python, including Jupyter, PyTorch, and common ML libraries.
- Have hands-on experience with compute clusters such as Ray or Slurm.
- Design trustworthy experiments to inform architectural decisions.
- Be able to drive features from concept to production with minimal supervision.
- Nice to have: familiarity with AWS, Azure, or GCP, particularly AI/ML deployment services.
- Nice to have: understanding of database systems and data processing pipelines; ClickHouse experience is a plus.
- Nice to have: experience with embedding-based systems such as retrieval, ranking, or recommenders.
Responsibilities
- Design and implement AI-powered features across backend inference services and frontend interfaces in ClickHouse Cloud.
- Create scalable APIs connecting ClickHouse database capabilities with AI/ML inference systems and other AI services.
- Implement and maintain integrations with AI/ML frameworks, tools, and standards.
- Integrate models into production systems with monitoring, versioning, observability, and evaluation.
- Own ML pipelines end to end, including data, training, and evaluation.
- Fine-tune or train custom models when off-the-shelf models fall short.
- Participate in the daytime on-call rotation.
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