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

Conditions

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