ML Engineer
Tasks
- Build analytical pipelines using cloud and distributed systems
- Develop marketing science solutions
- Ensure code quality testing documentation and reproducibility
- Manage deployments and debug production issues for models and pipelines
- Mentor peers and support engineering excellence
- Operationalize prototypes into production code
- Optimize models using high performance computing and real time techniques
- Standardize reusable scalable components for marketing analytics
- Stay current with ML infrastructure MLOps and AI tooling
Perks/Benefits
Skills/Tech-stack
AWS | As-a-Service | Azure | Cloud platform | Code optimization | Confluence | Containerization | Distributed Systems | Docker | Functions-as-a-service | Git | Google Cloud | Google Cloud Platform | High Performance | High-Performance Computing | Jira | MLOps | Parallelization | Performance Computing | Predictive Modeling | Python | R | Real Time | Real-time Systems | Statistical modeling | Time Systems
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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