Senior Machine Learning (ML) Engineer
USD 165K-218K Senior-level Full Time
Tasks
- Architect code deploy and iterate using Python based ML tooling
- Automate tracking analysis
- Build tracking intelligence infrastructure end to end
- Create autotuning capabilities for tracking parameters
- Deploy and version models for measurable tracking performance gains
- Develop human in the loop query tools
- Evaluate build vs leverage decisions for tracking intelligence models
- Identify correlation failures and tracking anomalies
- Instrument C plus plus tracking algorithms with logging
- Manage ML lifecycle data catalogs ground truth labeling and validation
- Marshal telemetry into consistent formats for analysis
- Package and deploy models for air gapped systems
- Translate tracking algorithms concepts into ML solutions
Perks/Benefits
- 401k match
- Caregiver leave
- Commuter benefits
- Dental benefits
- Generous time off
- Healthcare benefits
- Life and disability insurance
- Mental health resources
- Professional development reimbursement
- Relocation assistance
- Vision benefits
- Wellness leave
Skills/Tech-stack
Air-gapped | Air-gapped systems | Airflow | Anomaly Detection | Apache Spark | Automl | Autotuning | C plus plus | Cause analysis | Containerization | Dagster | Dask | Data Association | Data Catalog | Data Processing | Data pipeline | Distributed data | Distributed data processing | Docker | Edge Deployment | Experiment tracking | Feature Engineering | Feature extraction | Ground Truth | Ground Truth Labeling | Hyperparameter Tuning | Hypothesis tracking | Kalman Filters | Kubernetes | Logging | MLOps | MLflow | Model Registry | Model Validation | Model as Data Artifact | Model versioning | Multi-hypothesis Tracking | Online Learning | PyTorch | Python | Root Cause Analysis | Root cause | Scikit-learn | Streaming Data | TensorFlow | Time Series
Education
N/A
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