Principal ML Scientist
Tasks
- Architect and scale agentic AI systems
- Architect and scale generative AI systems
- Build data pipelines for model training
- Define technical strategy and architecture patterns
- Design and implement AI/ML platforms
- Lead development of Agentic AI solutions
- Train, evaluate, deploy, and monitor models
- Translate business challenges into AI powered solutions
Perks/Benefits
- 401k retirement plan
- Employee wellness days
- Healthcare benefits
- Life insurance
- Mental health or EAP programs
- Paid parental leave
- Paid time off
- Remote work options
- Tuition assistance
Skills/Tech-stack
Agent systems | Agentic AI | Cloud Platforms | Compliance | Data Pipelines | Distributed Systems | Experimentation | Generative AI | Governance | LLM orchestration | Language Models | Large Language Models | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Personalization | Predictive Modeling | Python | RAG | Ranking Models | Recommendation Systems | Responsible AI | Security | Software Engineering
Education
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