Full-Time

Inference Optimization Manager

Confirmed live in the last 24 hours

Wayve

Wayve

201-500 employees

Develops embodied AI for autonomous vehicles

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
  • Proven Leadership: 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
  • Expertise in AI and Embedded Systems: A solid understanding of AI model optimization techniques, edge computing, and embedded system design, ideally within the automotive or similar high-stakes industries
  • Technical Proficiency: Hands-on experience with AI model development and optimization tools such as PyTorch, CUDA, and TensorRT. Familiarity with programming languages including Python and C++
  • Strategic Thinking: Strong ability to develop and execute strategic plans for technology development, aligning with both short-term and long-term objectives
  • Collaborative Skills: Excellent interpersonal and communication skills, with a proven ability to foster collaboration across diverse technical teams.
  • Educational Background: 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
  • Team Leadership and Strategy: 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
  • Optimization Framework Development: 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
  • Cross-functional Collaboration: 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
  • Performance Benchmarking: Establish rigorous benchmarking standards for model performance, including computational efficiency, inference speed, and power consumption, guiding the team in achieving and surpassing these benchmarks
  • Innovation and Research: Promote a culture of continuous improvement and innovation, encouraging the team to explore novel optimization techniques, including quantization, model pruning, and advanced compiler technologies
  • Resource Allocation: Efficiently manage resources, including personnel and computing infrastructure, to meet project deadlines and performance targets
  • Talent Development: 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 a smarter and safer approach to autonomous vehicles. Their technology uses embodied AI software, allowing 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, providing them with 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

23%

1 year growth

67%

2 year growth

126%
Simplify Jobs

Simplify's Take

What believers are saying

  • Partnership with Uber enhances market reach and credibility for Wayve's technology.
  • Expansion into the U.S. market offers insights from diverse urban environments.
  • Strategic investment from SoftBank boosts financial resources for R&D and expansion.

What critics are saying

  • Increased competition in San Francisco could dilute Wayve's market presence.
  • Dependency on Uber partnership may pose risks if expectations aren't met.
  • Rapid tech advancements could render Wayve's technology obsolete if not updated.

What makes Wayve unique

  • Wayve uses embodied AI, enabling vehicles to learn and adapt without explicit programming.
  • Their AV2.0 technology eliminates the need for costly robotic stacks and complex mapping.
  • Wayve's GAIA-1 model enhances AI adaptability and learning in autonomous vehicle development.

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