Machine Learning Operations Engineer - Manager

AI / ML Engineer

Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : DevOps Architecture
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
As an AI / Machine Learning Engineer, a typical day involves designing and building advanced applications and systems that integrate artificial intelligence tools and cloud-based AI services. The role requires managing the development pipeline for both cloud and on-premises environments, ensuring solutions are production-ready and scalable. The engineer applies generative artificial intelligence models and may work on diverse technologies such as deep learning, neural networks, chatbots, and image processing. Collaboration with various teams to align technical solutions with project goals is a key aspect of daily activities, fostering innovation and efficiency in AI-driven projects.

Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead the integration of artificial intelligence models into scalable production systems.
- Mentor junior team members to support their professional growth and technical development.
- Coordinate cross-functional efforts to ensure alignment of AI infrastructure with organizational objectives.

Professional & Technical Skills:
- Must To Have Skills: Proficiency in DevOps Architecture.
- Experience with cloud platforms and deployment pipelines to support AI and machine learning workloads.
- Strong knowledge of automation tools and infrastructure as code to streamline development and operations.
- Familiarity with containerization and orchestration technologies to manage scalable AI applications.
- Ability to troubleshoot and optimize system performance in complex AI environments.
- Understanding of security best practices in cloud and on-premises AI infrastructure.

Additional Information:
- The candidate should have minimum 5 years of experience in DevOps Architecture.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.