AI Runtime and ML Model Systems Engineer

Houston, TX

Pay: Pay not listedSimilar roles state $166K–$240K
Work setting: Not stated
Employment: Not stated

What you’ll work on

We are looking for an AI Runtime / ML Model Systems Engineer to define the architecture and performance strategy for AI workloads across HP PCs.

Define runtime architectures and performance strategies for AI workloads across heterogeneous compute resources.

Define runtime architectures and performance strategies for AI workloads across CPU, GPU and NPU
Design runtime abstraction layers connecting apps and models to inference engines and hardware
Set model placement, scheduling and fallback policies across CPU, GPU and NPU
Evaluate ONNX Runtime, TensorRT and OpenVINO to guide framework selection
Define benchmarks and validation criteria using prototype and system measurements

From the employer’s posting

We are looking for an AI Runtime / ML Model Systems Engineer to define the architecture and performance strategy for AI workloads across HP PCs. You will determine how software should use compute engines, memory, hardware capabilities, and different model types to deliver reliable and responsive AI experiences. Working with platform architects and engineering teams, you will shape runtime abstraction frameworks, model placement policies, and execution strategies across CPUs, GPUs, and NPUs. You will translate product and experience requirements into architectural decisions that balance inference performance, resource availability, power consumption, and thermal constraints. This role emphasizes system design, technical planning, and architectural guidance. Success requires deep knowledge of AI runtime behavior and the ability to define solutions that engineering teams can implement and validate across different hardware configurations.

Define runtime architectures and performance strategies for AI workloads across heterogeneous compute resources.

Design runtime abstraction layers and interfaces that connect applications and models to inference engines and hardware backends.

Define model placement, scheduling, and routing policies across CPU, GPU, and NPU resources, including fallback behavior and resource availability considerations.

Evaluate inference technologies such as ONNX Runtime, TensorRT, and OpenVINO to guide framework selection and integration decisions.

Define benchmarks and validation criteria; use prototype results and system measurements to assess architectural choices.

What you’ll bring

All qualifications

Core experience

7+ years of experience in systems engineering, software architecture, AI runtimes, or a related field.
Experience designing AI runtime systems, inference platforms, or model execution frameworks for edge devices or other resource-constrained environments.
Strong understanding of how AI models use compute engines, memory, and hardware acceleration, including trade-offs across CPU, GPU, and NPU execution.
Experience with inference frameworks such as ONNX Runtime, TensorRT, or OpenVINO and an understanding of their hardware dependencies and execution behavior.
Ability to translate product and performance requirements into system architectures, interface definitions, and technical specifications.
Ability to guide cross-functional engineering teams and communicate architectural decisions and trade-offs clearly.

Preferred experience

Experience architecting AI runtime or system software for Windows PCs.
Familiarity with hardware acceleration backends and software ecosystems from Intel, AMD, NVIDIA, or Qualcomm.
Knowledge of different model architectures, quantization approaches, and their implications for compatibility, memory footprint, and execution.
Experience planning for resource contention, power and thermal constraints, and concurrent AI workloads.

Qualification wording

7+ years of experience in systems engineering, software architecture, AI runtimes, or a related field.

Experience designing AI runtime systems, inference platforms, or model execution frameworks for edge devices or other resource-constrained environments.

Strong understanding of how AI models use compute engines, memory, and hardware acceleration, including trade-offs across CPU, GPU, and NPU execution.

Experience with inference frameworks such as ONNX Runtime, TensorRT, or OpenVINO and an understanding of their hardware dependencies and execution behavior.

Ability to translate product and performance requirements into system architectures, interface definitions, and technical specifications.

Ability to guide cross-functional engineering teams and communicate architectural decisions and trade-offs clearly.

Experience architecting AI runtime or system software for Windows PCs.

Familiarity with hardware acceleration backends and software ecosystems from Intel, AMD, NVIDIA, or Qualcomm.

Knowledge of different model architectures, quantization approaches, and their implications for compatibility, memory footprint, and execution.

Experience planning for resource contention, power and thermal constraints, and concurrent AI workloads.

Education & alternatives

- Ability to guide cross-functional engineering teams and communicate architectural decisions and trade-offs clearly. - Bachelor’s degree in computer science, software engineering, information technology, a related field, or equivalent practical experience. Preferred Skills

About HP

At HP, you’ll have a chance to create tools, technology, and solutions that reshape the way the world works in the future.

In the employer’s words · Read in context

Apply at HP

Posting record

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Status in our records: Live
First seen by us: Oct 19, 202616 days ago
Recorded sightings: 33
Last seen by us: Nov 3, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 16

Similar jobs usually come down between day 6 and day 69.

From 4,331 similar postings that came down. Coming down is not always a hire.

HP is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

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C++
Python

Where the posting names them

- Experience planning for resource contention, power and thermal constraints, and concurrent AI workloads. - Familiarity with C++ and Python for evaluating technical feasibility, reviewing implementations, or developing architectural proofs of concept. - Knowledge of agentic applications, multiple-model execution, and local and cloud inference strategies.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About HP

At HP, you’ll have a chance to create tools, technology, and solutions that reshape the way the world works in the future. If you’re looking to join a company that allows you to connect with a network of professionals eager to support you in doing your best work, we want to talk to you. Our legendary culture guides every employee toward success—fostering collaboration and driving innovation.

Operating in over 170 countries, HP is always creating new services, products, and capabilities giving you more opportunities to advance your career. Here, innovation is the key to professional development and career mobility.

When you join HP, you’re joining a company that believes every voice matters and that we all deserve a seat at the table. From the boardroom to factory floor, we create a culture where everyone is respected and where people can be themselves. You will be part of a global laboratory where different perspectives and experiences will help you solve problems in new ways. This is where you can build a long and wide-ranging career.

About The Role

We are looking for an AI Runtime / ML Model Systems Engineer to define the architecture and performance strategy for AI workloads across HP PCs. You will determine how software should use compute engines, memory, hardware capabilities, and different model types to deliver reliable and responsive AI experiences. Working with platform architects and engineering teams, you will shape runtime abstraction frameworks, model placement policies, and execution strategies across CPUs, GPUs, and NPUs. You will translate product and experience requirements into architectural decisions that balance inference performance, resource availability, power consumption, and thermal constraints. This role emphasizes system design, technical planning, and architectural guidance. Success requires deep knowledge of AI runtime behavior and the ability to define solutions that engineering teams can implement and validate across different hardware configurations.

What You Might Do

Define runtime architectures and performance strategies for AI workloads across heterogeneous compute resources.
Assess how model types, hardware capabilities, memory requirements, and workload behavior should influence system design.
Design runtime abstraction layers and interfaces that connect applications and models to inference engines and hardware backends.
Define model placement, scheduling, and routing policies across CPU, GPU, and NPU resources, including fallback behavior and resource availability considerations.
Evaluate inference technologies such as ONNX Runtime, TensorRT, and OpenVINO to guide framework selection and integration decisions.
Establish approaches for memory allocation, model lifecycle management, and resource coordination when multiple AI workloads execute concurrently.
Translate product requirements into performance targets, system requirements, and architectural guidance for development teams.
Define benchmarks and validation criteria; use prototype results and system measurements to assess architectural choices.
Lead design reviews and collaborate with platform, security, and hardware and software partners to resolve dependencies and guide engineering roadmaps.

Essential Qualifications

7+ years of experience in systems engineering, software architecture, AI runtimes, or a related field.
Experience designing AI runtime systems, inference platforms, or model execution frameworks for edge devices or other resource-constrained environments.
Strong understanding of how AI models use compute engines, memory, and hardware acceleration, including trade-offs across CPU, GPU, and NPU execution.
Experience with inference frameworks such as ONNX Runtime, TensorRT, or OpenVINO and an understanding of their hardware dependencies and execution behavior.
Ability to translate product and performance requirements into system architectures, interface definitions, and technical specifications.
Strong software engineering fundamentals, including APIs, concurrency, memory management, and the interaction between operating systems and hardware.
Ability to guide cross-functional engineering teams and communicate architectural decisions and trade-offs clearly.
Bachelor’s degree in computer science, software engineering, information technology, a related field, or equivalent practical experience.

Preferred Skills

Experience architecting AI runtime or system software for Windows PCs.
Familiarity with hardware acceleration backends and software ecosystems from Intel, AMD, NVIDIA, or Qualcomm.
Knowledge of different model architectures, quantization approaches, and their implications for compatibility, memory footprint, and execution.
Experience planning for resource contention, power and thermal constraints, and concurrent AI workloads.
Familiarity with C++ and Python for evaluating technical feasibility, reviewing implementations, or developing architectural proofs of concept.
Knowledge of agentic applications, multiple-model execution, and local and cloud inference strategies.

Compensation & Benefits (Full-Time Employees)

The salary range for this role is listed above. Final salary offered is based upon multiple factors including individual job-related qualifications, education, experience, knowledge and skills.

At HP, we offer a competitive and comprehensive benefits package, 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)

Why join HP?

When you join HP, you’re investing in your future—and so are we. You have priorities beyond work. That’s why we offer flexibility, support, and benefits that help you shape the life you want.

Equal Opportunity Employer (EEO) Statement

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.

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