Senior MLOps Engineer - CI/CD Pipeline (10-14 yrs)

A leading company specializing in delivering cutting-edge AI and machine learning solutions. They are the world's first AI-powered tech services company. They have reimagined tech services from the ground up with AI by offering AI-vetted and matched talent, AI-accelerated development, and access to AI transformation experts who have built many of the most iconic Silicon Valley companies. Founded in 2018, the company has experienced tremendous growth. Their leadership team comprises both AI technologists from leading organizations including Meta, Google, Microsoft, Apple, Amazon, Twitter, Stanford, Caltech, MIT as well as tech consulting veterans from Accenture, Cognizant, Capgemini, McKinsey, Bain, and more.

Position : Sr. ML Ops Engineer

Total Experience : 10yr+

ML Op Experience : 2y - 4y (Must Have) and Dev Ops Experience: 6y - 9y (Must Have)

Work Mode : Fully Remote

Location : India

Joining : Immediate to 15 days

Work Timing : Monday through Friday for 8 hours each day. Upto 5 hours of overlap with PST time zone.

Interview Process : MCQ Quiz, 2/3 technical rounds and 1 final round

Job Description :

Seeking a seasoned ML Platform Engineer. This role involves designing and implementing scalable MLOps platforms for Fortune 500 clients, enabling seamless development, deployment, and maintenance of machine learning models. The successful candidate will leverage deep expertise in cloud platforms and DevOps practices to bridge the gap between data science and operations, contributing to transformative AI projects.

Job Responsibilities :

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

- Design and implement the overall architecture of the ML Ops 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.