Application SW Engineer at Wayve

Japan

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, AI, AutomotiveIndustries

Requirements

8+ years of experience in embedded or automotive software development, ideally with hands-on platform bring-up experience
Strong proficiency in C/C++, Bash, and Python
Deep understanding of Linux-based embedded systems (Yocto, systemd, bootloaders, device trees)
Familiarity with QNX and Adaptive AUTOSAR environments and the ability to configure and debug them on target hardware
Experience with bring-up on automotive-grade SoCs (e.g., NVIDIA Orin, Qualcomm SA8295/SA8650, Renesas, TI)
Comfortable working with hardware debuggers, flashing tools, serial consoles, and board support packages (BSPs)
Familiarity with communication protocols like CAN, Ethernet, PCIe, SPI, I2C
Hands-on experience integrating embedded platforms into CI/CD pipelines and test automation frameworks
Desired
Exposure to automotive verification environments (e.g., HIL systems, Vector toolchains, custom CI rigs)
Experience working in a safety-critical domain with an understanding of ISO 26262, boot

Responsibilities

Execute software bring-up on customer hardware platforms (e.g. NVIDIA Drive, Qualcomm Ride)
Port and configure Linux-based systems, QNX, and Adaptive AUTOSAR environments
Integrate and validate drivers, middleware, and boot-time configurations
Collaborate with Verification & Release teams to integrate hardware into CI/CD, HIL, and test infrastructure
Work with OEM and Tier 1 teams to resolve hardware-specific integration issues
Implement system-level diagnostics, logging, and secure boot configuration
Develop automation for setup, flashing, health checks, and test execution on target hardware

Skills

C++

Python

ROS

Linux

Embedded Systems

Autonomous Driving

AI Software

Hardware Integration

Software Validation

Real-time Systems

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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