Senior Machine Learning Researcher, On-Device Optimization

HyperX; Palo Alto (CA); On-site; USD 150,000 - 250,000; Full time

Job summary

A leading technology company, HyperX, is seeking a Senior Machine Learning Researcher to advance on-device AI optimization. This role involves implementing innovative model compression techniques and collaborating on cutting-edge technologies that enhance intelligent assistants on HP devices, offering a competitive salary and comprehensive benefits package.

Benefits

Health insurance

Dental insurance

Vision insurance

Flexible spending account

Generous parental leave

11 paid holidays

Flexible paid vacation

Qualifications

• PhD focusing on efficient ML, systems ML, or compiler design.
• 2+ years industry or applied research experience.
• Strong background in model optimization for edge computing.

Responsibilities

• Research and implement model compression techniques.
• Develop methods for deploying models on-device.
• Collaborate with engineers to integrate models into applications.

Skills

Model optimization

Quantization

Machine learning

Collaboration

Education

PhD in Computer Science

PhD in Electrical Engineering

Tools

PyTorch

ONNX

TensorRT

OpenVINO

Job description

Senior Machine Learning Researcher, On-Device Optimization page is loaded

Senior Machine Learning Researcher, On-Device Optimization

Apply locations Palo Alto, California, United States of America Boise, Idaho, United States of America Spring, Texas, United States of America time type Full time posted on Posted 17 Days Ago job requisition id 3152034 Senior Machine Learning Researcher, On-Device Optimization

Description -

Who We Are

HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates.

We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless.

We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset.

By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work.

Join us as we reinvent work, so people everywhere can do their best work.

About The Role

As a Machine Learning Researcher, you’ll focus on advancing the state-of-the-art in on-device AI optimization. This role bridges applied research and product development, with a heavy focus on techniques like quantization, pruning, and efficient model representation. You’ll bring academic expertise into real-world systems that power intelligent assistants running directly on HP laptops and edge devices.

What You Might Do

• Research and implement model compression techniques including quantization, low-rank factorization, distillation, and pruning
• Develop methods to deploy SOTA transformer and vision models on-device under hardware constraints
• Lead investigations into hardware-aware training strategies to optimize latency, throughput, and memory usage
• Collaborate with software engineers and system architects to integrate models into AI companion apps
• Evaluate and benchmark different frameworks and quantization strategies (e.g., AWQ, GPTQ, SmoothQuant)

Essential Qualifications

• PhD in Computer Science, Electrical Engineering, or related field with focus on efficient ML, systems ML, or compiler design for ML
• 2+ years of industry or applied research experience
• Strong background in model optimization for edge computing or mobile/embedded deployment
• Familiarity with PyTorch, ONNX, TensorRT, OpenVINO, QNN, or Llama.cpp
• Understanding of tradeoffs in asymmetric/symmetric quantization, calibration methods, and inference tuning

Preferred Skills

• Experience publishing at top ML/Systems conferences (e.g., NeurIPS, ICML, MLSys)
• Familiarity with embedded ML for consumer devices
• GPU and system-level profiling tools (e.g., CUDA, nvprof, perf)
• Contributions to open-source ML optimization frameworks

The pay range for this role is $150,000 to $250,000 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 )

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 -

Relocation -

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.

If you’d like more information about HP’sEEO Policy or your EEO rights as an applicant under the law, please click here:Equal Employment Opportunity is the Law Equal Employment Opportunity is the Law – Supplement

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