Manager - Machine Learning Ops (MLOps)

What you will do:

Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of internal stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable.

The core responsibilities of this role are:

• Leading a team of machine learning engineers to build, automate, deploy and scale ML models and pipelines in production.
• Enact ML and software development best practices for the team to follow.
• Monitoring performance and microservice health status of models in production.
• Partner with external stakeholders to prioritize, scope, and deliver ML solutions
• Perform additional duties as assigned. 

What you will need:

• Graduate education in a computationally intensive domain.
• 7+ years of prior relevant work or lab experience in ML projects/research
• 2+ years as tech lead or team management experience
• Advanced proficiency with Python and SQL (BigQuery/MySQL).
• Experience with building scalable REST APIs (Flask, FastAPI)
• Experience with building data pipelines (Airflow, Kubeflow, sklearn pipelines, etc.)
• Extensive knowledge of ML frameworks and libraries like Feast, XGBoost, PyTorch etc.
• Familiarity with cloud platforms and tools for scalable ML operations (e.g., AWS, GCP, Kubernetes).

Preferred Qualifications:

• Experience with ML model development lifecycles
• Prior contributions to data architecture or software architecture projects

  Role & responsibilities.