Senior Machine Learning Engineer, Multimodal Perception

Waymo

Mountain View, CA

Hybrid

Who this role is best for

Best suited to candidates with expertise in multi-modal deep learning and data curation working in autonomous vehicle perception systems.

Best fit for

Candidates with 2–5 years of experience in deploying multi-modal deep learning models for autonomous systems
— “2–5+ years training and deploying production vision or multi-modal deep learning models.”
Individuals skilled in building large-scale data curation and auto-labeling systems
— “Experience building large-scale data curation pipelines, active learning loops, and auto-labeling systems.”
Professionals with a strong background in transformer architectures and PyTorch/JAX frameworks
— “Experience with ... transformer architectures, and PyTorch / JAX.”

Things to consider

The role requires a strong focus on production deployment and real-world performance optimization
— “Architect, train, and optimize multi-task deep learning models ... for efficient onboard accelerator inference.”
The position involves working on safety-critical systems for autonomous vehicles
— “The Special Vehicle Compliance team develops ... that enables the autonomous vehicle to safely interact with high-stakes road actors.”

How to stand out

Highlight experience with multi-task learning and sensor fusion in autonomous systems
— “multi-task deep learning architectures for vehicle semantics and signal detection”
Emphasize contributions to large-scale data curation and automated labeling systems
— “Build automated data mining pipelines, active learning loops, hard-example curation, and auto-labeling systems.”
Showcase work with high-resolution vision backbones and spatial-temporal transformers
— “Develop high-resolution vision architectures and spatial-temporal transformer backbones.”
Demonstrate familiarity with multimodal foundation models for data generation and triage
— “Leverage multimodal foundation models for automated data curation, synthetic edge-case generation, and failure triage.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

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

What success looks like

Architect, train, and optimize multi-task deep learning models
Build automated data mining pipelines
Develop high-resolution vision architectures
Leverage multimodal foundation models for automated data curation

Typical background

2–5+ years training and deploying production vision or multi-modal deep learning models

Skills & requirements

Required

Multi-modal Sensor FusionMulti-task Deep LearningTransformer ArchitecturesPyTorchJAXLarge-scale Data Curation PipelinesActive Learning LoopsAuto-labeling Systems

Preferred

Multimodal Foundation ModelsAutomated Data Engines

Stack & domain

PyTorchJAXMulti-modal Sensor FusionMulti-task Learning (mtl)Transformer ArchitecturesLarge-scale Data Curation PipelinesActive Learning LoopsAuto-labeling SystemsHigh-resolution Vision ArchitecturesSpatial-temporal Transformer BackbonesMultimodal Foundation ModelsAutomated Data CurationSynthetic Edge-case GenerationFailure TriageModel Profiling And OptimizationLeadershipCommunicationProblem-solvingTeamworkAutonomous DrivingMachine LearningComputer Vision

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 Special Vehicle Compliance team develops the multi-modal perception, semantic reasoning, and driving intelligence that enables the autonomous vehicle to safely interact with high-stakes road actors. We are actively advancing our systems toward data-driven learned policies and end-to-end architectures, powered by large-scale closed-loop data engines.
Role overview: Perception-focused MLE role dedicated to multi-modal sensor fusion, multi-task deep learning architectures for vehicle semantics and signal detection, dynamic high-resolution vision backbones, and large-scale automated data engines.
In this hybrid role, you will report to the Technical Lead Manager of the Special Vehicle Compliance team.
You will:
Architect, train, and optimize multi-task deep learning models (PyTorch / JAX) across multi-modal sensor streams.
Build automated data mining pipelines, active learning loops, hard-example curation, and auto-labeling systems.
Develop high-resolution vision architectures and spatial-temporal transformer backbones.
Leverage multimodal foundation models for automated data curation, synthetic edge-case generation, and failure triage.
Profile and optimize models for efficient onboard accelerator inference.
You have:
2–5+ years training and deploying production vision or multi-modal deep learning models.
Experience with multi-modal sensor fusion (Camera + LiDAR + Audio), multi-task learning (MTL), transformer architectures, and PyTorch / JAX.
Experience building large-scale data curation pipelines, active learning loops, and auto-labeling systems.
Fluency with modern AI developer tools and foundation model workflows for fast prototyping.
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$213,000—$263,000 USD

Source: Waymo careers