Inference Optimization Manager

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

At Wayve, big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The Role :

As the Manager of the Inference Optimization team at Wayve, you will steer our pioneering efforts to refine and productize AI models for autonomous driving features in consumer vehicles. Occupying a critical junction between machine learning and embedded systems, you will lead the strategic direction and provide comprehensive oversight to a team committed to enhancing the efficiency and performance of our autonomous vehicle (AV) AI models to ensure their maximal performance on automotive embedded compute platforms. From the initial stages of development to the final phases of deployment, your expertise will ensure the seamless integration of AI into automotive technologies, requiring a profound grasp of AI model optimization, edge computing, and embedded systems within the automotive sector.

Key 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

Essential :

• 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.

This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.

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We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.