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Mlops Product Manager
Tata Consultancy ServicesAtlanta, GA, United States30+ days ago
Job type
- Full-time
Job description5+ years of experience in product management, preferably with a focus on ML Ops, data science, or machine learning infrastructure . Strong understanding of ML Ops tools and platforms, including ML pipelines, CI / CD, model versioning, and monitoring frameworks. Technical expertise in machine learning, data engineering, and DevOps methodologies Experience with cloud platforms (AWS, Azure, Google Cloud) and their ML services, data platforms like BigQuery. Familiarity with Agile methodologies and project management tools (e.g., Jira, Github). Experience developing with containers and Kubernetes in cloud computing environments Exposure to write, run SQL queries to validate data availability & quality Experience of reading through code repos to understand logic Experience in managing, tracking progress across key MLOps stages : data sourcing, feature engineering, model training including hyperparameter tuning if any, testing and deployment. Exposure to Vertex AI, MLFlow, Kubeflow Exposure to implementing model governance frameworks & reproducibility standards. Exposure to setting up / interpreting dashboards for model performance.
Preferred -
- Knowledge of model interpretability and explain ability tools and techniques.
- Experience in data privacy and compliance as it relates to ML.
- Prior experience with large-scale ML system deployments.
- Product Strategy & Roadmap : Define and prioritize the ML Ops product roadmap by assessing business goals, customer needs, and emerging industry trends in ML Ops.
- Cross-functional Collaboration : Work closely with data scientists, ML engineers, DevOps, and software engineers to ensure seamless integration and deployment of ML models.
- Project Management : Coordinate and manage timelines, resources, and deliverables across multiple teams to keep projects on track.
- Model Lifecycle Management : Oversee the end-to-end ML model lifecycle, including data preparation, model development, deployment, monitoring, and maintenance.
- Automation & Scaling : Identify opportunities for automation and scalability in the ML pipeline, from data ingestion to model deployment.
- Monitoring & Optimization : Develop and implement monitoring and alerting frameworks for model performance and data quality. Partner with engineering teams to troubleshoot and optimize pipelines.
- Stakeholder Communication : Serve as the primary point of contact for internal and external stakeholders. Communicate product updates, metrics, and results to senior leadership.
- Risk Management : Identify, assess, and mitigate risks related to ML model deployment, including ethical considerations, data privacy, and regulatory compliance.
- Documentation & Training : Develop clear and comprehensive documentation for ML Ops processes and workflows. Provide training to teams on best practices.
Roles & Responsibilities :
LI-RJ2
Salary Range - $100,000-$150,000 a year
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Product Manager • Atlanta, GA, United States