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  • Senior Machine Learning Researcher, On-Device…

    HP Inc. (Boise, ID)



    Apply Now

    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 (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.

     

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

     


    Apply Now



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