Description
We're looking for an ML Ops Engineering Manager to drive the architecture, implementation, and evolution of our machine learning operations. This is a hybrid role blending technical execution and strategic leadership, ideal for someone who thrives on impact and innovation.
The successful candidate will define and drive the technical vision for MLOps in alignment with enterprise goals, build and maintain end-to-end ML pipelines and CI/CD workflows for scalable model deployment, lead and grow a high-performing MLOps team, and partner cross-functionally with Data Science, Engineering, and DevOps teams to seamlessly integrate ML models into production.
Key responsibilities include:
- Defining and driving the technical vision for MLOps in alignment with enterprise goals.
- Building and maintaining end-to-end ML pipelines and CI/CD workflows for scalable model deployment.
- Leading and growing a high-performing MLOps team, fostering a culture of best practices and continuous improvement.
- Partnering cross-functionally with Data Science, Engineering, and DevOps teams to seamlessly integrate ML models into production.
The ideal candidate will have proven experience in MLOps and machine learning infrastructure, hands-on expertise with Python and AWS (SageMaker, Lambda, etc.), strong background in CI/CD, model versioning, monitoring, and automation, and a passion for scalable systems and enabling ML success across the organization.
This position comes with a competitive compensation and benefits package, including a comprehensive benefits package, career development and training opportunities, flexible work arrangements, and a dynamic and inclusive work culture within a globally renowned group.