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HP Inc. seeks an AI/ML Platform Engineer to advance a centralized platform for Generative AI and large language models. You will build internal tools, APIs, and CI/CD, while provisioning AWS/Azure resources and troubleshooting deployments.
You will collaborate across teams, design scalable architectures, and guide model deployment to production using SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes. Expected 7–10 years of related experience with strong coding and ML expertise.
AI/ML Platform Engineer
We are a dynamic centralized platform team dedicated to harnessing cutting-edge AI/ML technology, particularly in the realm of Generative AI and large language models, to empower HP and drive innovation. Collaborating closely with various business units, we provide strategic advice, prototype solutions, and develop and manage software applications tailored for internal use.
Days split roughly evenly between hands-on building and collaboration/enablement, driven by a mix of roadmap work and incoming requests. Expect to shift context often.
Internal platform tools and services: self-service portals/workbenches, backend APIs (Python/FastAPI), automations and CI/CD tooling
MCP/gateway integrations and AI-enabled automations and flows
Focus is always on reducing friction for teams adopting the platform
Writing and maintaining Terraform; provisioning and configuring platform resources across AWS and Azure
Diagnosing deployment, networking, endpoint, and configuration issues
Enough depth to reason about deployments and partner with security/networking specialists
Standups, syncs, and planning/project meetings
Design and architecture reviews; regular PR and code review
Onboarding new teams; translating ambiguous requirements into practical plans and challenging weak designs
Documentation, onboarding guides, and reference examples
Ad-hoc process and platform improvements—spotting and fixing rough edges proactively
a builder-first role with a strong collaborative and enablement component—someone who moves fluidly between writing code, reviewing work, troubleshooting infrastructure, and guiding architectural decisions.
Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
Typically has 7-10 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field.
AWS Certified Machine Learning Specialty
The pay range for this role is $147,050 to $230,850 USD annually with additional
opportunities for pay in the form of bonus and/or equity (applies to United
States of America candidates only). Pay varies by work location, job-related
knowledge, skills, and experience.
Benefits:
The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time,
with or without notice, subject to applicable law.
Software
Full time
No shift premium (United States of America)
No
No
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 (https://www8.hp.com/h20195/v2/GetDocument.aspx?docname=c08129225) or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal (http://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)