ML Ops Engineer

Description -

Position background:

In the GTM analytics COE our mission is to deliver impact by building machine learning products to optimize pricing and marketing investments and provide guidance to our sales organization.

This role sits within the Internal ML Platform / Enablement team, responsible for building and operating shared ML infrastructure used by multiple data science and engineering teams across the organization. You will work within established patterns and standards, contributing to the reliability, scalability, and compliance of our ML platform.

This role is well suited for engineers with 2–4 years of experience who want to deepen their skills in ML Ops, ML infrastructure, and platform operations in a regulated, enterprise environment.

We offer international experience, collaborative culture, top rate experience in AI and ML and opportunity to create significant real-world impact.

What will you do:

• Contribute to the development and operation of the internal ML platform

• Maintain and improve ML workloads on Databricks, Spark, and AWS

• Support experiment tracking, model packaging, and deployment workflows

• Develop and maintain CI/CD pipelines for ML use cases

• Deploy and operate services on Kubernetes using Docker and Helm

• Development, maintenance and optimization of Python libraries following best practice standards.

• Participate in L2 support for platform-related incidents

• Follow and contribute to shared engineering standards and documentation

• Collaborate with data science and engineering teams across the organization

• Ensure compliance with internal security and regulatory requirements

What you will need:

• Bachelor's in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field

• 2–4 years of experience in ML Ops, DevOps, Data Platform, or Software Engineering

• Strong working knowledge of SQL, PostgreSQL, Python

• Hands-on experience with Docker and Kubernetes

• Familiarity with CI/CD pipelines (GitHub Actions preferred)

• Exposure to ML workflows and tools such as ML flow, Databricks, or Spark

• Understanding of ML fundamentals and production ML lifecycles

• Experience working with enterprise or regulated environments

• Ability to work effectively within existing systems and architectural patterns

• Experience with modern application lifecycle management tools (Git, Visual Studio, Intellij, Code Reviews).

• Experience in deploying REST API services

Nice to have:

• Experience contributing to shared internal platforms

• Experience with AWS, Open Search, Grafana

• Experience with Python Libraries e.g. Pandas or Polars

• Experience using Terraform or other Infrastructure-as-Code tools

• Exposure to monitoring and observability for ML systems

• Experience supporting production platforms (L2 or similar)

• Experience in Test-Driven-Development (TDD)

Job -

Schedule -

Shift -

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Relocation -

Equal Opportunity Employer (EEO) - 

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"