Overview
The Senior MLOps Engineer will play a critical role in enhancing the machine learning capabilities of an organization by building and scaling its next-generation ML platform. This remote contract position emphasizes hands-on involvement in productionizing machine learning solutions, creating deployment pipelines, and developing infrastructure that supports Data Science teams effectively. Collaborating with Data Scientists, Platform Engineers, and Software Engineers, this position will influence platform design and engineering standards while driving advancements in MLOps across the business.
Responsibilities
- Design, build and maintain infrastructure for deploying machine learning models into production.
- Develop and maintain Python APIs using FastAPI and/or Flask.
- Build and enhance CI/CD pipelines for machine learning deployment workflows.
- Implement monitoring, observability, and model lifecycle management processes.
- Collaborate with Data Scientists to productionize models and improve deployment reliability.
- Build scalable cloud-native solutions using modern engineering best practices.
- Contribute to infrastructure automation through Infrastructure as Code.
- Drive improvements in platform performance, resilience, security, and maintainability.
Requirements
- Strong experience as an MLOps Engineer.
- Proven experience deploying and maintaining machine learning models in production environments.
- Strong software engineering fundamentals with Python development experience.
- Experience building APIs and production-grade backend services.
- Familiarity with Agile development environments.
- Strong problem-solving skills and ability to work independently on complex technical challenges.
- Experience with GCP (Vertex AI preferred).
- Proficiency with Terraform, Docker, and Git.