AI Runtime and ML Model Systems Engineer
HP
Salary undisclosed
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Description
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
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Define runtime architectures and performance strategies for AI workloads across heterogeneous compute resources.
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Assess how model types, hardware capabilities, memory requirements, and workload behavior should influence system design.
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Design runtime abstraction layers and interfaces that connect applications and models to inference engines and hardware backends.
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Define model placement, scheduling, and routing policies across CPU, GPU, and NPU resources, including fallback behavior and resource availability considerations.
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Evaluate inference technologies such as ONNX Runtime, TensorRT, and OpenVINO to guide framework selection and integration decisions.
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Establish approaches for memory allocation, model lifecycle management, and resource coordination when multiple AI workloads execute concurrently.
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Translate product requirements into performance targets, system requirements, and architectural guidance for development teams.
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Define benchmarks and validation criteria; use prototype results and system measurements to assess architectural choices.
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Lead design reviews and collaborate with platform, security, and hardware and software partners to resolve dependencies and guide engineering roadmaps.
Essential Qualifications
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7+ years of experience in systems engineering, software architecture, AI runtimes, or a related field.
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Experience designing AI runtime systems, inference platforms, or model execution frameworks for edge devices or other resource-constrained environments.
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Strong understanding of how AI models use compute engines, memory, and hardware acceleration, including trade-offs across CPU, GPU, and NPU execution.
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Experience with inference frameworks such as ONNX Runtime, TensorRT, or OpenVINO and an understanding of their hardware dependencies and execution behavior.
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Ability to translate product and performance requirements into system architectures, interface definitions, and technical specifications.
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Strong software engineering fundamentals, including APIs, concurrency, memory management, and the interaction between operating systems and hardware.
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Ability to guide cross-functional engineering teams and communicate architectural decisions and trade-offs clearly.
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Bachelor’s degree in computer science, software engineering, information technology, a related field, or equivalent practical experience.
Preferred Skills
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Experience architecting AI runtime or system software for Windows PCs.
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Familiarity with hardware acceleration backends and software ecosystems from Intel, AMD, NVIDIA, or Qualcomm.
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Knowledge of different model architectures, quantization approaches, and their implications for compatibility, memory footprint, and execution.
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Experience planning for resource contention, power and thermal constraints, and concurrent AI workloads.
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Familiarity with C++ and Python for evaluating technical feasibility, reviewing implementations, or developing architectural proofs of concept.
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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.
Benefits
- health insurance
- dental insurance
- vision insurance
- parental leave
- life insurance
- disability insurance
- professional development
- sick leave
About this role
HP is seeking an AI Runtime and ML Model Systems Engineer to architect how artificial intelligence workloads will run across its PC ecosystem. This role sits at the intersection of hardware and software, where you'll define the runtime strategies and system designs that determine how AI models execute on CPUs, GPUs, and NPUs while managing power, thermal, and memory constraints. Rather than implementing these systems yourself, you'll establish the architectural framework and performance targets that guide engineering teams, working closely with platform architects and hardware partners to translate product requirements into concrete technical specifications.
The position demands deep expertise in AI inference platforms and runtime behavior—you should have hands-on experience with frameworks like ONNX Runtime, TensorRT, or OpenVINO and understand how different model types and hardware accelerators interact. Beyond technical depth, you'll need to communicate architectural trade-offs clearly to cross-functional teams and lead design reviews that resolve dependencies across security, platform, and hardware groups. This is fundamentally a systems design and technical planning role, not a coding-heavy position, though familiarity with C++ and Python for prototyping and feasibility assessment is valuable.
The role is based in Houston and requires in-office work. You'll need at least seven years in systems engineering, software architecture, or AI runtimes, ideally with experience optimizing for resource-constrained environments like edge devices. Windows PC experience and knowledge of Intel, AMD, NVIDIA, or Qualcomm ecosystems are preferred but not required.
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Pay for this role
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