AI/ML Platform Engineer - Build, Deploy & Scale AI

HP Inc.; United States; On-site; USD 147,000 - 231,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Disability insurance

Employee assistance program

Flexible spending account

Life insurance

Parental leave

Paid holidays

Vacation and sick leave

Job summary

HP Inc. seeks an AI/ML Platform Engineer to build and operate scalable platform services for internal use, including backend APIs, automation tooling, and CI/CD pipelines. You will enable teams with reliable deployment patterns across SageMaker, Bedrock, Azure ML, and Kubernetes.

The role blends hands-on coding with collaboration, architecture reviews, and platform improvements, shifting focus between code, troubleshooting, and design decisions.

Qualifications

• Four-year degree or graduate degree in CS/Math/Stats/Data Science or related field.
• 7–10 years of work experience in programming, ML, algorithms or related field.
• AWS Certified Machine Learning Specialty is preferred.

Responsibilities

• Build and maintain internal platform tools and services (Python/FastAPI, CI/CD).
• Work on MCP/gateway integrations and AI-enabled automations.
• Troubleshoot deployments, networking, and configuration issues across AWS/Azure.
• Collaborate in design/architecture reviews and guide teams on implementations.
• Support model deployment: hosting options, inference patterns, scaling, and operations.
• Create and improve documentation and onboarding guides.

Skills

Agile Methodology

Algorithms

Amazon Web Services

Apache Spark

Artificial Intelligence

Automation

Big Data

C++

Computer Science

Data Science

Deep Learning

Java

Machine Learning

Microsoft Azure

Natural Language Processing

Python

PyTorch

Scikit-learn

Software Engineering

TensorFlow

Education

Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or related field

Job description

HP Inc. seeks an AI/ML Platform Engineer to build and operate scalable platform services for internal use, including backend APIs, automation tooling, and CI/CD pipelines. You will enable teams with reliable deployment patterns across SageMaker, Bedrock, Azure ML, and Kubernetes.

The role blends hands-on coding with collaboration, architecture reviews, and platform improvements, shifting focus between code, troubleshooting, and design decisions.