Machine Learning (ML) / Data Engineer
Tasks
- Build and maintain APIs and services
- Build ingestion transformation and storage pipelines
- Collaborate with stakeholders on requirements
- Create containers and deployments
- Deploy models and workflows
- Design production machine learning systems
- Develop ETL/ELT pipelines
- Develop model evaluation scaffolding
- Document system operational instructions
- Ensure model governance and reproducibility
- Implement MLOps pipelines
- Implement data orchestration and scheduling
- Implement data validation and cleansing
- Implement model inference services
- Integrate models into applications
- Monitor model performance
- Prepare datasets and feature pipelines
- Set up CI/CD pipelines
- Translate analytical requirements into ML services
- Write automated tests
Perks/Benefits
- 401k plan
- Catered lunches
- Dental and vision plans
- Medical plans
- Onsite fitness center
- Training opportunities
- Wellness program
Skills/Tech-stack
APIs | CI/CD | Containerization | Data Cleansing | Data Modeling | Data Preprocessing | Data Validation | Data Visualization | ELT | ETL | Feature Engineering | Feature Pipelines | Inference | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Performance Tuning | Python | SQL | Software testing | Statistical Analysis | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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