Level

HP

AI/ML Platform Engineer

AI in this role

bedrockpytorchtensorflowscikit-learnsagemaker
nlp
AI/ML Platform Engineer

Description -

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.

Building (largest share of the day)

  • 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

Cloud infrastructure & troubleshooting (weekly)

  • 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

Collaboration & enablement (about half the day)

  • 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

Model deployment support (recurring)

  • Helping teams productionize models—hosting options, inference patterns, scaling, cost, and operational readiness across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes

Docs & platform improvement (ongoing)

  • Documentation, onboarding guides, and reference examples
  • Ad-hoc process and platform improvements—spotting and fixing rough edges proactively

In short: 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.

Education & Experience Recommended

  • 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.

Preferred Certifications

AWS Certified Machine Learning Specialty

Knowledge & Skills

• Agile Methodology

• Algorithms

• Amazon Web Services

• Apache Spark

• Artificial Intelligence

• Automation

• Big Data

• C++ (Programming Language)

• Computer Science

• Data Science

• Deep Learning

• Java (Programming Language)

• Machine Learning

• Microsoft Azure

• Natural Language Processing

• Python (Programming Language)

• PyTorch (Machine Learning Library)

• Scikit-learn (Machine Learning Library)

• Software Engineering

• TensorFlow

Cross-Org Skills

• Effective Communication

• Results Orientation

• Learning Agility

• Digital Fluency

• Customer Centricity

Pay & Benefits

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:

HP offers a comprehensive benefits package for this position, including:

  • Health insurance
  • Dental insurance
  • Vision insurance
  • Long term/short term disability insurance
  • Employee assistance program
  • Flexible spending account
  • Life insurance
  • Generous time off policies, including;
  • 4-12 weeks fully paid parental leave based on tenure
  • 11 paid holidays
  • Additional flexible paid vacation and sick leave
  • US benefits overview https://hpbenefits.ce.alight.com/

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.

Job -

Software

Schedule -

Full time

Shift -

No shift premium (United States of America)

Travel -

No

Relocation -

No

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"

How we rate this

AI/ML Platform Engineer at HP rates 19 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

NLPBedrockPyTorchTensorFlowscikit-learnSagemaker

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Walk me through how you've used Bedrock in your day-to-day work.
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: NLP, Bedrock, PyTorch, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.

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