Key Responsibilities
- Design, implement, and deploy new features and enhancements to ML products in collaboration with Product and ML Research teams
- Provide technical ownership of production ML products, ensuring alignment with business goals and engineering best practices
- Contribute to the evolution of the shared ML platform, driving best practices and shared tooling across products
- Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging for high operational standards
- Conduct code reviews to enforce standards, improve quality, and share knowledge
- Identify and implement process, tooling, and system improvements to address technical debt and scaling challenges
Requirements
- 5+ years as an ML Engineer or MLOps Engineer with hands-on production experience
- Expertise in ML model deployment, API design, and integration into production environments
- Strong Python programming and relevant ML/data libraries
- Experience with containerization, orchestration, and AWS cloud services
- Building and operating CI/CD pipelines (Jenkins preferred)