Senior MLOps Engineer

Senior MLOps Engineer

Description -

Are you passionate about technology and looking to work in an agile start-up environment that is built on the brand recognition, solution capabilities, and global reach of a world-class technology pioneer? The HP Workforce Solutions (HPWS) team operates in a highly dynamic landscape that delivers a best-in-class, multi-OS Services portfolio powered by software, cloud, data analytics, and machine learning.

The AI Systems team within HPWS is seeking a passionate Senior MLOps Engineer who will be an integral part of the team responsible for the architecture, deployment, and optimization of our AI/ML platform and delivering stellar customer experiences and solutions, using one of the largest data lakes in the world.

As an MLOps Engineer at HP, you will collaborate closely with data scientists, software engineers, DevOps engineers, and IT specialists. Your expertise will ensure the robustness, reliability, and scalability of our ML infrastructure, ultimately enhancing HP's Workforce Solutions portfolio powered by cutting-edge software, cloud, data analytics and machine learning technologies.

Key Responsibilities:

• Architect, develop, and maintain advanced ML platforms within an end-to-end MLOps framework.
• Optimize model development and streamline deployment workflows.
• Design and implement scalable infrastructure solutions for high-performance computing and large-scale data processing.
• Establish CI/CD pipelines for automated training, testing, and deployment (end-to-end solutions).
• Collaborate with cross-functional teams, including Data Science, DevOps and Product, synchronizing MLOps strategies with overarching corporate objectives.
• Create stories and visualizations to describe and communicate technical concepts in a simple manner.
• Work closely with product management to understand product vision and user engagement strategy for the HPWS Managed Insights Team.
• Provide regular updates to key stakeholders about progress, road blocks, and risks.
• Act as subject matter expert through internal training and demonstration of key product functionality for support, sales, onboarding, and other cross-functional teams.
• Implement quick and effective action plans to meet short-term priorities and emerging opportunities.
• Influence decision making and problem solving across HPWS.
• Conduct A/B testing and experimentation.

Knowledge and Skills:

• Expert knowledge of Python, Spark, and SQL.
• Strong experience in cloud computing and MLOps, especially tools such as AWS (SageMaker, EMR, Redshift, S3, Lambda), Docker, Airflow, GitHub, Azure DevOps, and Jira.
• Strong analytical and problem-solving skills.
• Fluency in structured and unstructured data, its management, and modern ETL methodologies.
• Deep understanding of current machine learning concepts and tools.
• Ability to deal with ambiguity and work collaboratively in a fast-paced environment.
• Ability to work efficiently in both virtual and in-person team environments.
• Hands-on technical skills with the inquisitiveness to learn products, experiment with them, and provide recommendations to drive continuous improvement.
• Ability to both work independently and collaborate cross-functionally in a global and multicultural environment.
• Ability to manage multiple work streams effectively and provide timely updates to leadership.
• Comfort with working in new areas that require experimentation and rapid problem solving.

Preferred:

• Deep experience using AWS SageMaker tools for MLOps, such as Experiments, Model Registry, Pipelines, Model Monitor, Canvas, and Clarify
• Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, and/or Scikit-Learn
• Experience with other MLOps and DevOps platforms, such as Azure, Google Cloud, MLflow, KubeFlow, Jenkins, Splunk, Kafka, and Terraform
• In-depth knowledge of one or more applications of deep learning, such as generative AI (ex. LLMs), recommendation systems, or computer vision.
• Understanding of security and compliance requirements in ML infrastructure.
• Experience with Microsoft Graph API.

Education and Experience:

• Master's degree or Ph.D. in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, Physics, etc.)

• 4+ years of industry experience.

Job -

Software

Schedule -

Full time

Shift -

No shift premium (United States of America)

Travel -

Relocation -

EEO Tagline -

HP Inc. is EEO F/M/Protected Veteran/ Individual with Disabilities.