Senior Applied AI & Data Scientist
Tasks
- Apply responsible AI practices and audit ready controls
- Build agentic workflows and multi step orchestration
- Communicate insights and tradeoffs to stakeholders
- Contribute to reusable MLOps LLMOps standards
- Define evaluation plans and success criteria
- Design and deliver LLM enabled analytics using RAG
- Develop and deploy statistical and machine learning models
- Engineer feature pipelines and embeddings
- Own end-to-end delivery of AI solutions
- Productionize and operate models with monitoring
Perks/Benefits
- 401-k match
- Certifications support
- Childbirth leave
- Company Funded Retirement Plan
- Dental insurance
- Employee assistance program
- Flexible workweek schedules
- Health club reimbursement
- Health insurance options
- Health savings account
- Life insurance
- Long-term disability
- No visa sponsorship
- Paid Holidays
- Parental leave
- Remote work
- Short-term disability
- Tuition reimbursement
- Vacation and paid sick leave
- Vision insurance
Skills/Tech-stack
A/B | A/B Testing | Agentic Workflows | Audit controls | B testing | Bias and fairness | CI/CD | Cortex | Deep learning | Docker | Documentation | Drift Detection | Embeddings | FastAPI | Feature Engineering | Flask | Function Calling | Human-in-the-loop | Hybrid search | LLMOps | MLOps | MLflow | Machine Learning | Model Cards | Model Governance | Monitoring | PostgreSQL | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Scikit-learn | Snowflake | Snowpark | TensorFlow | The Loop | Vector Databases | Vector Search | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
Cities
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