Sr. Machine Learning Engineer
Tasks
- Architect end-to-end ML systems
- Build training pipelines
- Contribute to long term ML strategy and architecture decisions
- Deploy model-serving infrastructure
- Design train deploy machine learning models
- Drive responsible AI practices
- Ensure reproducibility
- Establish model evaluation standards
- Implement experiment tracking
- Implement robust monitoring and alerting
- Lead technical design reviews
- Mentor junior machine learning engineers
- Monitor model performance
- Optimize model performance and inference cost
- Participate in hiring and team building
- Partner with data platform for feature requirements
- Translate business problems into production ML solutions
- Troubleshoot production model drift degradation pipeline failures
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | BigQuery | CI/CD | Code review | Databricks | Experiment Management | Experiment tracking | Feature Engineering | Feature Store | GCP | Generative AI | Infrastructure as Code | LLM | MLOps | MLflow | Model Governance | Model Monitoring | Model Serving | Model lineage | PyTorch | Python | RAG | SQL | Snowflake | TensorFlow | Testing | Training pipelines | Vector Database | Version control | “as-code”
Education
N/A
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