Principal Applied Scientist
Tasks
- Architect AI solutions for data training serving and evaluation
- Build agentic workflows with reliability and guardrails
- Coordinate engineering teams for reliable production readiness
- Develop and optimize LLM prompt workflows and tool calling
- Drive end to end ML and deep learning model development
- Establish MLOps best practices for production deployment
- Implement monitoring drift detection and regression testing
- Productionize models with scalable inference and APIs
- Provide technical leadership in reviews planning and retrospectives
- Translate business requirements into ML and LLM problem statements and evaluation plans
Perks/Benefits
- Adoption Assistance
- Disability insurance
- Flexible spending accounts
- Life insurance
- Medical, dental, and vision insurance
- Paid Holidays
- Paid parental leave
- Paid sick leave
- Paid time off
- Retirement plan match
Skills/Tech-stack
API Design | Automated testing | CI/CD | Containerized inference | Data Quality | Data handling | Deep learning | Drift Detection | Error Analysis | Feature Engineering | Fine Tuning | Function Calling | Generative AI | Hyperparameter Tuning | Language Models | Language Processing | Large Language Models | Latency optimization | MLOps | Machine Learning | Model Evaluation | Model versioning | Natural Language | Natural Language Processing | Observability | PEFT | Prompt engineering | RAG Embeddings | Retrieval-Augmented Generation | Secure Data | Secure Data Handling | Throughput Optimization | Tool-Calling
Education
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