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Karkidi

Staff Machine Learning Engineer, Model Optimization

Karkidi, Mountain View, CA, United States


We are looking for a staff engineer with model optimization expertise to help us improve compute performance on our car. You'll work across the entire ML stack from models, to ML frameworks/libraries, to different HW platforms. You will collaborate with the world-class scientists and engineers in Waymo, Google, Deepmind and will be pleasantly challenged with the state-of-the-art model compression technologies.

In this role you'll:

  1. Lead the collaboration with the world-class Waymo ML scientists in perception, planner, research and simulation. Build productive relationships and understand their models. Identify opportunities in both systems and models to make ML workloads faster.
  2. Lead projects from proposals, through goals and execution, to results. Lead and mentor junior engineers.
  3. Deep dive into the full stack of ML software stack. Analyze the ML workload performance. Apply model optimization, efficient deep learning techniques and ML software improvements.
  4. Collaborate on foundation models and ML System with external partners such as CoreML, Google Brain and Deepmind.

At a minimum, we'd like you to have:

  1. S. in CS, EE, Deep Learning or a related field
  2. 2+ years of experience as a technical lead
  3. 3+ years of experience on model optimization or efficient deep learning techniques
  4. Strong Python or C++ programming skills
  5. Thorough understanding of key ML system challenges and trade-offs.
  6. Solid experience with designing, training and debugging deep learning models to achieve the highest scores/accuracies.

It’s preferred if you have:

  1. PhD in CS, EE, Deep Learning or a related field.
  2. Proven track record on efficient deep learning and/or model optimization techniques with foundation models.
  3. Deep knowledge on system performance, GPU optimization or ML compiler.
  4. 5+ years of experience on model optimization or efficient deep learning techniques.

LI-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range: $226,000—$286,000 USD

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