Senior ML Ops Engineer

You will be instrumental in architecting data solutions, designing and optimizing data pipelines, and operationalizing machine learning models. This position requires a strong technical foundation, strategic thinking, and the ability to collaborate across disciplines to drive innovation and data-driven excellence.

In this role, you will take lead in creating high-quality backend architectures that leverage cloud technologies. Your architectural vision will be a blend of business acumen, performance optimization, cost-efficiency, and practical implementation.

As the Lead, you will orchestrate the project’s technical directions, ensuring alignment with overarching goals while guiding and mentoring your colleagues. You will nurture a collaborative environment where team members thrive and feel empowered. You will be responsible for helping the organization upskill for upcoming needs in the evolving landscape of Machine Learning Ops and Generative AI.

You will get the ability to be creative in the world of big data technology without the encumberment of a large-scale organization. You will have the freedom to explore the latest technologies out there to not only improve your own skillset, but also help the organization improve.

Requirements

• Strong experience with containerization, orchestration, CI/CD deployment and the AWS cloud platform.
• Machine learning operations project experiences with relevant experience in SageMaker.
• Good understanding of databases/warehouses.
• Previous experience deploying data products end to end.
• Experience with implementing governance frameworks, data privacy regulations, and compliance standards.
• Previous experience architecting efficient processing frameworks.
• Proven leadership experience in machine learning operations, including managing teams responsible for model deployment, monitoring, and maintenance.
• Ability to collaborate with cross-functional teams and drive technical decisions.
• Excellent communication and leadership skills.