Principal Machine Learning Engineer - Autonomy at Wayve

Sunnyvale, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, AI, AutomotiveIndustries

Requirements

7+ years (Staff) or 10+ years (Principal) in ML engineering, with a strong track record of shipping deep learning systems to production
Expert in deep learning (esp. sequential models, control, planning, or perception)
Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices
Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components
Ability to lead technical initiatives across teams, drive alignment, and mentor engineers
Prior work in autonomous driving, imitation learning, or trajectory prediction (desirable)
Familiarity with personalization, human behavior modeling, or driver intent inference (desirable)
Experience integrating ML systems into production hardware or multi-agent simulation (desirable)

Responsibilities

Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization
Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment
Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness
Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development
Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems
Collaborate cross-functionally across various teams to ensure integration and iteration velocity
Mentor senior engineers and shape the long-term technical direction across Autonomy

Skills

Key technologies and capabilities for this role

Machine LearningAutonomous DrivingEmbodied AIModel ArchitectureData PipelinesAI Foundation ModelsReinforcement Learning

Questions & Answers

Common questions about this position

What does the company culture at Wayve emphasize?

Wayve is committed to a diverse, fair, and respectful culture that is inclusive of everyone based on their unique skills and perspectives, valuing diversity, embracing new perspectives, and fostering an inclusive work environment where contributions matter and team members back each other.

What are the main responsibilities of this Principal Machine Learning Engineer role?

The role involves developing end-to-end driving models, leading projects on personalized and collaborative driving, building evaluation pipelines, curating data, influencing architecture choices, and collaborating cross-functionally while mentoring engineers.

Is this position remote or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a strong candidate for this Principal Machine Learning Engineer position?

A strong candidate should have principal-level expertise in machine learning for autonomous driving, experience leading complex ML projects, skills in model architecture, data pipelines, evaluation, and deployment, plus the ability to mentor engineers and collaborate cross-functionally.

Wayve

Develops autonomous vehicle technology using AI

About Wayve

Wayve.ai develops self-driving technology known as AV2.0, which focuses on creating a smarter and safer approach to autonomous vehicles. Their technology uses embodied AI software that allows vehicles to learn from their experiences and adapt to different environments without needing detailed programming. This method is different from traditional self-driving technologies that often rely on expensive hardware and pre-mapped data. Instead, Wayve.ai employs end-to-end deep learning, making their solution more cost-effective for automakers. The company targets automakers and fleet operators, offering them adaptable and affordable solutions for driving automation. Wayve.ai has already partnered with major retailers in the UK to test its technology in delivery fleets, aiming to enhance mobility and sustainability in the automotive industry.

London, United KingdomHeadquarters

2017Year Founded

$1,272.3MTotal Funding

SERIES_CCompany Stage

Automotive & Transportation, AI & Machine LearningIndustries

201-500Employees

Benefits

Hybrid Work Options

Risks

Increased competition in San Francisco could dilute Wayve's market presence.

Regulatory challenges may delay the deployment of Wayve's technology with Uber.

Wayve's reliance on AI systems may face skepticism from traditional automakers.

Differentiation

Wayve uses embodied AI to adapt vehicles to any environment without explicit programming.

Its AV2.0 technology eliminates the need for costly robotic stacks and complex mapping.

Wayve's end-to-end deep learning approach offers a cost-effective solution for automakers.

Upsides

Wayve's partnership with Uber expands its market reach and data collection opportunities.

The expansion into the U.S. market taps into a larger talent pool and partnerships.

Generative AI models like GAIA-1 offer new ways to simulate driving scenarios.

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