What are the responsibilities and job description for the Tech Lead, ML Compiler Engineer position at Wayve?
The role
As the Tech Lead for the ML Compiler team, 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 for Wayve’s ML Compiler and GPU kernel development. From the initial stages of development to the final phases of deployment, your expertise will ensure the seamless integration of AI into automotive embedded devices, requiring a strong foundation in AI model optimization, edge computing, and embedded systems.
Key responsibilities:
- You will lead a multi-disciplinary team of ML compiler and kernel engineers, breaking down large milestones into objectives which can be delivered by yourself and the team
- As a hands-on engineer, you will deliver critical roadmap milestones in enabling efficient inference on multiple target GPUs and accelerators
- You will work closely with members of the ML and Software teams to optimise models for deployment on edge
- You will have opportunities to develop new skills, especially in model optimisation
About you
In order to set you up for success as a Tech Lead in ML Compilation at Wayve, we’re looking for the following skills and experience.
Essential:
- Proven experience as a technical lead or senior engineer on complex engineering projects
- Experience developing ML compilers and/or GPU kernels (e.g. TensorRT, MLIR, TVM, CUDA, OpenCL, etc)
- Proficiency in C , Python
- Proficiency with ML frameworks such as PyTorch
- Excellent interpersonal and communication skills
- Ability to mentor and guide a team of engineers
Desirable:
- Experience with ML deployment pipelines
- Experience with embedded SoCs used in automotive environments, e.g. Nvidia, Qualcomm, Renesas, etc
This is a full-time role based in our office in Sunnyvale. 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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