Principal Machine Learning Researcher, On-Device Optimization

HPPalo Alto, CA
2d$150,000 - $250,000

About The Position

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.

Requirements

  • 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

Nice To Haves

  • 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

Responsibilities

  • 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)

Benefits

  • 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)

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What This Job Offers

Job Type

Full-time

Career Level

Principal

Education Level

Ph.D. or professional degree

Number of Employees

5,001-10,000 employees

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