ML Ops Engineer​/Lead

We are seeking an individual with proven experience as an MLOps/Dev Ops Engineer to drive our organization's ML Ops strategy in support of the broader AI strategy. The successful candidate will play a critical role in shaping & scaling our AI/ML capabilities.

• Oversee and manage the build and maintenance of robust and scalable ML pipelines.
• Design and implement automated workflows for data ingestion, model training, deployment, monitoring, and governance.
• Collaborate with data scientists and engineers to ensure seamless integration of ML models into production environments using Kubernetes services.
• Develop and implement best practices for ML platform security, reliability, and performance.
• Monitor and assess model performance and implement corrective actions.
• Stay informed about the latest trends and technologies in ML Ops and advocate for their adoption.
• Build and maintain a collaborative and high‑performing team culture, fostering continuous learning and growth.
• Communicate effectively with stakeholders at all levels, both technical and non‑technical, to provide clear insights on ML operations.

• 5+ years of experience in ML Ops or a related field.
• Proven track record of building and managing ML pipelines, including data preparation, model training, deployment, and monitoring.
• Solid foundation in Dev Ops principles and practices with experience in CI/CD pipelines for ML deployments.
• Solid programming skills in Python or another scripting language.
• Experience working with model performance monitoring and troubleshooting.
• Strong understanding of data engineering principles and experience.
• Experience with MLOps platforms like MLflow and Kubeflow.
• Experience with relevant ML frameworks (e.g., Tensor Flow, PyTorch).
• Experience with containerization technologies like Docker and Kubernetes.
• Excellent communication, interpersonal, and collaboration skills.
• Strong assessment and problem‑solving skills.
• Ability to oversee and mentor a team.
• Passion for ML and its potential to solve real‑world problems.

• Experience with cloud‑based ML services like Azure Sage Maker and AutoML.
• Understanding of Azure stack such as Azure Machine Learning, Azure Data Factory, Azure Databricks, Azure Kubernetes Service, Azure Monitor, etc.
• Understanding of security and compliance requirements in ML infrastructure.

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

USD Annual Salary: $ - $

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and affirmatively action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are based on qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

Please :
Equal Employment Opportunity.