Staff Machine Learning Engineer, Multi-Modal Perception

Waymo
Mountain View +2 more
Hybrid

Who this role is best for

Best suited to mid-level machine learning engineers with computer vision expertise working in autonomous vehicle perception systems.

Best fit for

  • ML engineers with a track record of scaling real-world perception tasks
    — “Own tasks in the ML Driver, take responsibility for task scaling
  • Researchers who bridge academic rigor with production system constraints
    — “Publications at top-tier conferences like CVPR, ICCV, ECCV
  • Candidates comfortable with both Python and C++ ecosystems
    — “Experience with Python... Experience with C++

Things to consider

  • Hybrid reporting structure requires comfort with technical leadership
    — “In this hybrid role you will report to a Technical Lead Manager
  • Performance monitoring extends beyond model metrics to safety-critical issues
    — “Develop and maintain metrics for ADV relevant issues, including safety-critical

How to stand out

  • Demonstrate experience with large-scale real-world data pipelines
    — “develop methods for efficiently and continuously learning from large scale real-world data
  • Show concrete examples of production ML system debugging
    — “develop AI-aided analysis and debugging tooling
  • Highlight multi-modal sensor fusion experience if applicable
    — “diverse set of sensors, enabling engineers like you to
Pace · SteadyCollaboration · MediumAutonomy · HighDecision Impact · CompanyLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • develop ML methods and recipes
  • monitor ML systems in production
Typical background
machine learningcomputer science

Skills & requirements

Required

Machine LearningComputer VisionPythonPyTorchJAX

Preferred

C++Publications In Top-tier Conferences

Stack & domain

PythonPyTorchJaxMachine LearningComputer VisionCommunicationProblem-solvingTeamworkLeadershipAutonomous DrivingAI

About the role

Original posting from Waymo

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.

In this hybrid role you will report to a Technical Lead Manager.

You will:

Own tasks in the ML Driver, take responsibility for task scaling and task performance, create ML methods and recipes to scale and improve tasks.

Analyze behavior of ML systems in real-world application, identify issues and root causes, advise or develop short- and long-term solutions.

Monitor ML systems in production, develop methods for automatically detecting issues or regressions, develop AI-aided analysis and debugging tooling.

Develop and maintain metrics for ADV relevant issues, including safety-critical and longtail issues.

You have:

Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience

5+ years experience in Machine Learning and Computer Vision

Experience with Python

Experience with ML frameworks like PyTorch or JAX

We prefer:

MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline

Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI

Experience with C++

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$251,000—$310,000 USD

Source: Waymo careers

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