Engineer developing algorithms and optimizations for NVIDIA's inference and compiler stack. Working at the intersection of large - scale systems, compilers, and deep learning.
About the role
- MLOps Engineer building and maintaining a Cloud platform for public health initiatives. Collaborating with Agile teams to develop automated ML solutions for critical operations.
Responsibilities
- Build, configure, and maintain a robust MLOps platform in the Cloud
- Design and implement continuous integration and continuous deployment (CI/CD) workflows
- Work closely with an Agile development team
- Enhance and manage ML lifecycles
- Develop containerized applications
- Utilize distributed and cloud technologies such as Azure and Databricks
- Identify new opportunities to design and implement end-to-end automated data and ML pipelines
- Continuously evaluate and integrate new tools and technologies
Requirements
- 4+ years of experience with Object-Oriented Programming (OOP), including in Python or PySpark
- 3+ years of experience developing software using distributed and cloud technologies, including Azure and Databricks
- 3+ years of experience leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows
- Experience developing containerized applications, including API design and authentication
- Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem
- Bachelor's degree
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
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