Principal ML Scientist
Tasks
- Architect and scale generative AI systems
- Build data pipelines for model training and evaluation
- Define technical strategy and reusable architecture patterns
- Deploy and monitor machine learning models
- Design and implement end to end AI ML platforms
- Implement model governance and responsible AI controls
- Lead development of Agentic AI solutions
- Translate business challenges into scalable AI powered solutions
Perks/Benefits
- Employee stock purchase plan
- Paid time off
- Parental leave
- Remote work options
- Tuition assistance
- Wellness days
Skills/Tech-stack
Agent systems | Agentic AI | Claude Code | Cloud Platforms | Data Pipelines | Data Science | Distributed Systems | Experimentation | Generative AI | Language Models | Large Language Models | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Governance | Model Training | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Orchestration | Personalization | Predictive Modeling | Python | Ranking Models | Recommendation Systems | Retrieval-Augmented Generation | Software Engineering
Education
Roles
AI/ML Scientist | ML Scientist | Principal | Principal AI/ML Scientist | Scientist
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