About the Role
Wayve is seeking a Senior Machine Learning Performance Engineer to join our Machine Learning Platform team. This role is pivotal in optimizing large-scale training jobs as we aim to scale our models to the next order of magnitude. The Machine Learning Platform team is responsible for our GPU training infrastructure and the software abstractions around it. Your primary focus will be on improving training efficiency.
Key Responsibilities
- Maximize MFU: Work on maximizing the Machine Fractional Utilization (MFU) of our large-scale training jobs.
- Code Profiling: Profile and identify bottlenecks in training code to enhance performance.
- GPU Kernel Implementation: Implement GPU kernels to improve training throughput.
- Collaboration: Work closely with research teams to integrate and test training efficiency improvements.
- Cluster Management: Own and improve our GPU training clusters.
About You
Essential Qualifications:
- Over 5 years of experience in performance optimization or machine learning engineering.
- Proven experience in optimizing large-scale training jobs on GPU compute clusters.
- Experience working in platform teams and collaborating with research teams.
- Ability to report and track benchmarked performance over time in an open and accessible way.
- Proficiency in writing high-quality, well-structured, and tested Python code.
- BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline, or equivalent experience.
Desirable Skills:
- Solid experience with concurrent, parallel, and distributed computing.
- Experience using Nvidia NSight Systems.
- Experience implementing GPU kernels.
- Knowledge of computing fundamentals, including what makes code fast, secure, and reliable.
Why Join Us?
At Wayve, we are committed to creating a diverse, fair, and respectful culture that is inclusive of everyone based on their unique skills and perspectives. We value diversity, embrace new perspectives, and foster an inclusive work environment. Join us to tackle today's most complex challenges and pave the way for a smarter, safer future.
Work Environment
This is a full-time role based in our office in Mountain View, California. We operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships, and learning, with time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.
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.
Benefits Extracted with AI
- Hybrid working policy
- Core working hours
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