Eaton Corporation is looking for an Engineering Manager - Machine Learning to lead a team of Engineers focused on deploying and monitoring machine learning models in production. You will architect and implement end-to-end machine learning pipelines and establish best practices for MLOps.
What You'll Do
- Lead and manage a team of Engineers to deploy and monitor machine learning models in production.
- Work with data engineers for designing data engineering pipelines and performing robust ETL processes.
- Collaborate with cross-functional teams to understand business requirements and translate them into scalable ML solutions.
- Architect and implement end-to-end machine learning pipelines for model training, testing, deployment, and monitoring.
- Establish best practices and standards for model versioning, deployment, and monitoring.
- Implement automated processes for model training, hyperparameter tuning, and model evaluation using tools such as Weight and Biases, MLflow, Kubeflow, or similar.
- Design and implement infrastructure for scalable and efficient model serving and inference, leveraging technologies such as Kubernetes, Docker, and serverless computing.
- Develop and maintain monitoring and alerting systems to detect model drift and performance degradation.
- Provide technical leadership and mentorship to team members.
- Stay current with emerging technologies and industry trends in machine learning engineering.
- Collaborate with product management to define requirements and priorities for machine learning model deployments.
- Implement monitoring and logging solutions to track model performance metrics and system health.
- Lead efforts to optimize resource utilization and cost-effectiveness of machine learning infrastructure.
- Foster a culture of innovation, collaboration, and continuous improvement within the AI Operations team.
What We're Looking For
- B.Tech / M.Tech in Computer Science, Electronics or related fields.
- 8+ years of experience in machine learning and software development.
- Experience in research and development, technology strategy, global project management, team management, mentoring, and risk management.
Nice to Have
- Masters or Bachelor's degree in Computer Science, Engineering, or related field.
- 8+ years of experience in software engineering, data engineering, or related roles, with at least 2 years in a managerial or leadership role.
- Experience in designing and maintaining scalable data engineering pipelines and performing robust ETL processes.
- Previous experience in a leadership or management role, with a track record of successfully leading technical teams.
- Experience with version control systems (e.g., Git) and collaboration tools (e.g., GitHub, GitLab).
- Familiarity with infrastructure as code (IaC) tools such as Terraform or CloudFormation.
- Knowledge of software development methodologies (e.g., Agile, DevOps) and best practices.
- Ability to effectively communicate technical concepts to non-technical stakeholders.
- Strong proficiency in Python, JAVA and related IDEs.
- Awareness of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with cloud platforms and services (e.g., Azure, AWS, GCP).
- Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
- Hands-on experience with MLOps tools and platforms such as Weight and Biases, MLflow, Kubeflow, TFX, or similar.
- Experience in DevOps and DevSecOps tools and practices.
- Strong problem-solving skills and ability to troubleshoot complex issues in production environments.
- Excellent communication and collaboration skills.
Technical Stack
- Languages: Python, JAVA
- ML Frameworks: TensorFlow, PyTorch, scikit-learn
- Cloud Platforms: Azure, AWS, GCP
- Containerization & Orchestration: Docker, Kubernetes
- Version Control & Collaboration: Git, GitHub, GitLab
- Infrastructure as Code: Terraform, CloudFormation
- MLOps Tools: Weight and Biases, MLflow, Kubeflow, TFX
Eaton Corporation is an equal opportunity employer.
