Senior Software Engineer, Simulation at Wayve

Sunnyvale, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, AI, AutomotiveIndustries

Requirements

Domain experience in simulation, motion planning, localization, controls, modern machine learned graphics techniques (NeRF, Gaussian Splatting, or GenAI) or other areas of robotics
Good development skills in Python and C++, including modern C++ (11, 14, 17, 20)
Good sense of systems and data oriented software engineering design - what makes code reusable and extensible
Understanding of common software performance issues and design tradeoffs
5+ years of industry experience designing and programming software
Excellent communication and people engagement skills
(Desirable) Experience in the field of autonomous vehicles
(Desirable) Experience with simulating / modelling the dynamics of vehicles and robots
(Desirable) Experience with simulating / modelling real sensors (lidar, radar, gnss, etc...)

Responsibilities

Own key performance indicators (KPIs) for simulator realism, reproducibility, and/or cost
Work cross-company on aligning technical dependencies for simulator implementation
Lead technical discussions and guide technical direction
Effectively integrate the components of the simulated robot into the simulation platform
Effectively integrate machine-learned graphics subsystems into the simulation platform
Implement production quality software in C++ and Python
Shape and implement the technical roadmap in one of three key areas: robot emulator fidelity, visual fidelity, or efficient scaling

Skills

Simulation

Software Engineering

Autonomous Driving

Embodied AI

End-to-End Driving Stack

Foundation Models

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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