Full-Time

Inference Optimization Manager

Updated on 11/19/2024

Wayve

Wayve

201-500 employees

Develops autonomous vehicle technology using AI

Automotive & Transportation
AI & Machine Learning

Senior

London, UK

Hybrid working policy requires time in the office in London.

Category
Applied Machine Learning
Robotics & Autonomous Systems
AI & Machine Learning
Required Skills
Python
CUDA
Pytorch
C/C++
Requirements
  • At least 5 years of experience in a leadership role within the fields of machine learning, embedded systems, or a related area, with a track record of managing high-performing technical teams
  • A solid understanding of AI model optimization techniques, edge computing, and embedded system design, ideally within the automotive or similar high-stakes industries
  • Hands-on experience with AI model development and optimization tools such as PyTorch, CUDA, and TensorRT
  • Familiarity with programming languages including Python and C++
  • Strong ability to develop and execute strategic plans for technology development, aligning with both short-term and long-term objectives
  • Excellent interpersonal and communication skills, with a proven ability to foster collaboration across diverse technical teams
  • A Master's degree in Computer Science, Electrical Engineering, or a related field is required. A Ph.D. is highly preferred, along with a robust record of relevant research.
Responsibilities
  • Spearhead a multidisciplinary team of Machine Learning Engineers, Embedded Kernel Engineers, and Software Engineers, setting clear objectives and milestones for optimization projects.
  • Drive the vision and strategy for deploying cutting-edge AI models in AV systems, ensuring alignment with Wayve's overarching goals
  • Oversee the creation and refinement of optimization frameworks that enhance the computational efficiency of AI models while maintaining or improving model accuracy and inference speed
  • Facilitate seamless cooperation between the machine learning, software engineering, and embedded systems teams. Ensure that model development and optimization efforts are synchronized with hardware capabilities and deployment requirements
  • Establish rigorous benchmarking standards for model performance, including computational efficiency, inference speed, and power consumption, guiding the team in achieving and surpassing these benchmarks
  • Promote a culture of continuous improvement and innovation, encouraging the team to explore novel optimization techniques, including quantization, model pruning, and advanced compiler technologies
  • Efficiently manage resources, including personnel and computing infrastructure, to meet project deadlines and performance targets
  • Recruit, mentor, develop, and retain your team, fostering a growth mindset and technical excellence. Identify skill gaps and champion training and recruitment efforts to build a world-class inference optimization team

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

59%

2 year growth

115%
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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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