Staff Machine Learning Engineer - Autonomy at Wayve

London, England, United Kingdom

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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 LearningDeep LearningAutonomous DrivingModel ArchitectureData PipelinesEmbodied AIFoundation ModelsAI Evaluation

Questions & Answers

Common questions about this position

What will I be working on as a Staff Machine Learning Engineer in the Autonomy team?

You'll develop and improve end-to-end driving models, lead projects on personalized and collaborative driving, build evaluation pipelines, curate data, influence architecture choices, collaborate cross-functionally, and mentor senior engineers.

What is the salary or compensation for this Staff Machine Learning Engineer role?

This information is not specified in the job description.

Is this Staff Machine Learning Engineer position remote or does it require office work?

This information is not specified in the job description.

What is the company culture like at Wayve?

Wayve fosters a diverse, fair, respectful, and inclusive culture that values unique skills and perspectives, embraces uncertainty and complex challenges, aims high while staying humble, and backs team members to deliver impact in a fast-paced environment.

What skills or experience make a strong candidate for this role?

Strong candidates will have expertise in developing end-to-end ML models for autonomous driving, leading projects on personalized driving behaviors, building evaluation pipelines, curating data, influencing ML architectures, and collaborating cross-functionally while mentoring engineers.

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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