Senior Machine Learning Engineer
CA San Francisco 153 Kearny Street, United States
USD 159K-295K Senior-level Full Time
Tasks
- Apply causal inference uplift and propensity scoring
- Automate retraining and enforce training serving consistency
- Build scalable feature and inference pipelines
- Champion MLOps best practices with MLflow
- Define architectural decisions and trade off analysis
- Design feature store strategy with feature contracts
- Design production machine learning systems
- Develop offline and online experiment frameworks
- Implement drift detection and production monitoring
- Lead end to end data sourcing and feature engineering
- Mentor engineers through code reviews and design discussions
- Prototype agentic ML workflows and automate ML tasks
- Train, evaluate, deploy, and monitor models
- Translate business priorities into executable machine learning roadmap
- Use AI assisted development for code generation and documentation
Perks/Benefits
- N/A
Skills/Tech-stack
AUC-ROC | AWS | AWS SageMaker | Calibration Curves | Causal Inference | Clean room | Data clean room | Databricks | Delta | Delta Lake | Drift Detection | Embeddings | Feature Engineering | Feature Store | GitHub Copilot | Gradient boosting | Isotonic Regression | Langchain | Langgraph | LightGBM | MLOps | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Model Training | NDCG | Neural Networks | Precision-recall | Propensity score | PySpark | Python | RAG | SQL | Snowflake | Snowflake Data Clean Room | Snowflake data | Two Tower Retrieval | Two-Tower | Unity Catalog | Uplift Modeling | XGBoost
Education
Regions
Countries
States
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