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Full-Time

Engineering Manager

Simulation

Updated on 10/11/2024

Wayve

Wayve

201-500 employees

Develops autonomous vehicle technology using AI

Automotive & Transportation
Energy

Senior

London, UK

Hybrid working policy requires time in the office in London.

Category
Engineering Management
Software Development Management
Requirements
  • Proven track record of managing engineering teams.
  • Experience leading simulation, robotics, NeRF or GenAI development.
  • Experience with roadmap planning, stakeholder management, requirements gathering and alignment with peers towards milestones and deliverables.
  • Track record of promoting software engineering best practices and excellence within the team.
  • Demonstrated ability to manage software engineers and grow their careers.
  • Good foundational coding knowledge and experience.
Responsibilities
  • Help define and drive simulation roadmap to deliver on company goals and priorities
  • Lead technical discussions and guide technical direction where needed
  • Set effective KPIs and metrics
  • Build resilient and reliable systems, and teams, anticipate the needs of the business 18 months out, identify areas where additional resources are needed and grow team as hiring manager
  • Prioritise effectively, implement and maintain lean and effective team processes
  • Communicate effectively with internal stakeholders, and other teams within the organisation to ensure alignment.
  • Work closely with team members to develop career plans and growth trajectories.
  • Actively foster and promote technical excellence within the team.
  • Partner with leadership to maintain a culture of impact, performance, and health.

Wayve.ai develops self-driving technology known as AV2.0, which focuses on creating smarter and safer 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 aims to enhance mobility by partnering with companies like Ocado Group and Asda to test their technology in real-world delivery scenarios.

Company Stage

Series C

Total Funding

$1.3B

Headquarters

London, United Kingdom

Founded

2017

Growth & Insights
Headcount

6 month growth

38%

1 year growth

50%

2 year growth

101%
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Simplify's Take

What believers are saying

  • Wayve.ai's recent $1.05 billion funding round underscores strong investor confidence and provides substantial capital for further innovation and expansion.
  • The launch of PRISM-1, a 4D reconstruction model, enhances the testing and training of their autonomous driving technology, potentially accelerating development timelines.
  • Partnerships with major retailers and fleet operators offer significant opportunities for real-world testing and rapid deployment of their technology.

What critics are saying

  • The autonomous vehicle sector is highly competitive, with major players like Tesla and Nvidia investing heavily in similar technologies, which could impact Wayve.ai's market share.
  • The reliance on end-to-end deep learning and embodied AI, while innovative, may face challenges in regulatory approval and public acceptance.

What makes Wayve unique

  • Wayve.ai's use of embodied AI software allows vehicles to learn and adapt from experience, eliminating the need for costly HD maps and human-engineered systems, unlike traditional autonomous vehicle technologies.
  • Their end-to-end deep learning approach reduces the reliance on expensive robotic stacks, making their solution more cost-effective for automakers.
  • Wayve.ai's partnerships with leading UK retailers like Ocado Group and Asda for trialing their technology in delivery fleets demonstrate their practical, real-world application and scalability.

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