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.

What You'll Do:

• 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 service.
• 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.

About You:

• 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 Python or other scripting language.
• Experience working with on 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.

Desired

Skills:

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

Additional

Skills:

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Bias, Business, Coaching, Creativity, Critical Thinking, Cybersecurity, Data Analysis Management, Data Collection Management, Data Controls, Design Thinking, Development Methodologies, Empathy, Follow-Through, Growth Mindset, Implementation Methodologies, Infrastructure Design, Intellectual Curiosity, Long Term Planning, Managing Ambiguity {+ 4 more}

What We Can Offer You:

Health & Wellbeing

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.

Personal & Professional Development

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.

Diversity, Inclusion & Belonging

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.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

United States

technologyandsoftware

Job:

Information Technology

Job Level:

Master

States with Pay Range Requirement

The expected salary/wage range for a U.S.

-based hire filling this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. If this is a sales role, then the listed salary range reflects combined base salary and target-level sales compensation pay. If this is a non-sales role, then the listed salary range reflects base salary only. Variable incentives may also be offered.

Information about employee benefits offered can be found at

USD Annual Salary: $ - $

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative 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 made on the basis of 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.