Principal Data Scientist
Tasks
- Analyze model behavior and telemetry
- Build prototypes and proof of concepts
- Collaborate with engineers to productionize models prompts pipelines
- Create model evaluation frameworks test sets benchmarks
- Define data requirements and responsible AI considerations
- Deploy models to production services
- Design and execute experiments
- Develop applied AI solutions
- Document designs and share knowledge
- Evaluate machine learning models
- Implement RAG and agentic systems
- Improve model quality accuracy reliability latency cost safety
- Monitor AI quality and behavior
- Support incident analysis and continuous improvement
- Train and fine-tune models
Perks/Benefits
- 401k match
- Adoption Assistance
- Dental insurance
- Employee stock purchase plan
- Health insurance
- Life insurance
- Long-term disability
- Paid Holidays
- Paid parental leave
- Paid sick leave
- Paid time off
- Short-term disability
- Vision insurance
Skills/Tech-stack
Agentic AI | Benchmarking | Cost Optimization | Data Engineering | Data Pipelines | Data Preparation | Embeddings | Experiment design | Fine Tuning | Generative AI | Language Models | Large Language Models | Latency optimization | Machine Learning | Model Evaluation | Model Serving | Model Training | Prompt engineering | Python | Retrieval-Augmented Generation | Safety | Statistical modeling | Vector Databases
Education
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