Senior Machine Learning Platform Engineer - DevOps (10-15 yrs)

Job Description :

- Evaluate and select appropriate cloud services for each stage of the ML lifecycle.

- Design and implement the overall architecture of the MLOps platform.

- Set up automated pipelines for data preparation, model training, and deployment.

- Implement version control for code, data, and models to maintain reproducibility and traceability.

- Ensure the platform is scalable, secure, and compliant with relevant regulations.

- Provide tools and interfaces for data scientists to easily leverage the platform.

- Continuously optimize the platform for performance and cost-efficiency.

- Develop tools and interfaces for data scientists to easily utilize the platform's capabilities.

- Bridge the gap between data science and operations, enabling efficient development, deployment, and maintenance of ML models at scale.

Job Requirements :

- Bachelor's/Master's degree in Engineering, Computer Science, or equivalent experience.

- At least 10+ years of professional experience in building cloud-based applications, including ML platforms.

- Extensive expertise in cloud platforms like AWS, Google Cloud Platform, or Azure (Azure preferred).

- Proficiency in DevOps practices, including CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code.

- Strong understanding of ML workflows, model training, deployment processes, and data engineering pipelines.

- Advanced programming skills, particularly in Python, with a focus on ML applications.

- Experience in designing secure, scalable systems that adhere to regulatory compliance.

- Demonstrated ability to collaborate with cross-functional teams, including data scientists and software engineers.

Total Years Of exp : 10+ years experience mandatory

Recent Experience: 2-4 years in ML Ops.

Previous Experience: Remaining years in DevOps.

Opportunity : Full time, 4 - 5 hours (PST overlap)

Notice Period : 2 weeks only