ML Engineer
Tasks
- Build data pipelines feature stores and model serving infrastructure
- Design train evaluate and ship ML systems for governance and security
- Develop evaluation harnesses and feedback loops
- Own model lifecycle and shipping bar
- Participate in on call rotation for ML services
- Set ML architecture and evaluation methodology standards
Perks/Benefits
- Equity
- Flexible work schedule
- Holidays
- Home office setup
- Medical benefits
- PTO
- Paid parental leave
- Remote-first culture
- Retirement plan
- Technology stipend
- Training stipend
Skills/Tech-stack
Anomaly Detection | Artificial Intelligence | Data Pipelines | Feature Stores | Fine Tuning | Fraud Detection | LLM guardrails | Language Models | Language Processing | Large Language Models | Machine Learning | Model Evaluation | Model Serving | Monitoring | Natural Language | Natural Language Processing | Policy recommendations | Prompt engineering | Retrieval-Augmented Generation | Trust Scoring
Education
Roles
Regions
Countries
States
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