Machine Learning Engineer
Tasks
- Apply engineering standards and best practices
- Apply machine learning and AI techniques
- Build and maintain data pipelines
- Build and optimize machine learning and AI models
- Collaborate using code reviews and design reviews
- Define ML AI modules and build definitions
- Define model metrics and acceptance criteria
- Deploy automation for build and release processes
- Design develop test and document ML programs
- Elicit requirements for ML AI lifecycle practices
- Evaluate and monitor model performance
- Identify issues in models pipelines and datasets
- Implement model and pipeline improvements
- Implement opportunities to improve training data and features
- Maintain machine learning and AI pipelines
- Monitor progress and report risks blockers and dependencies
- Refactor and maintain ML code
- Select and implement lifecycle practices for microservices
- Support monitoring of emerging technologies
- Validate ML AI modules against quality criteria
Perks/Benefits
Skills/Tech-stack
Apache Airflow | Argo Workflows | Artificial Intelligence | CI/CD | Cloud Computing | Containerization | Data Pipelines | Deployment | DevOps | Docker | ELT | ETL | Experiment tracking | FastAPI | Kubernetes | Langchain | MLOps | Machine Learning | Microservices | Model Evaluation | Model Packaging | Monitoring | Next.js | NoSQL | Pydantic | Python | REST APIs | SQL | TypeScript | Version control
Education
N/A
Regions
Countries
States
Cities
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