Software Engineer, ML Accelerators
Google DeepMind · Mountain View, CA, USA · San Francisco, CA, USA
Frontier labonsite$174k–$252k
At a glance
Highlights
- Building a next-generation compute platform for AI inference workloads.
- Bridging AI workloads to low-level hardware for high-performance inference.
- Driving hardware/software co-design to optimize performance and debugging.
What they offer
- 15% bonus target
- Equity
- Benefits
Ideal candidate
Initiative-driven engineer who loves full-stack systems work and HW/SW co-design to advance AI inference, thriving in ambiguous, collaborative environments.
Requirements
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience
- Experience in software development using Python and C++
- Experience with ML hardware accelerators, ML compiler stacks and kernel development
- PhD in Computer Engineering, Computer Science, or related field (preferred)
- 2 years of experience with full-stack system development for hardware accelerators (preferred)
- 2 years of experience with collaborative, hyper-scalar software development and engineering best practices (preferred)
- Experience scoping, planning, and executing projects towards team goals in ambiguous environments (preferred)
Lab profile
About Google DeepMind
Google's AI lab building frontier models like Gemini to advance science and general intelligence.
What they build
- Gemini
- Gemma
- AlphaFold
Known for
- Frontier foundation models and GenAI
- Large-scale training with JAX, PyTorch, TensorFlow
- Model evaluation and deployment expertise
- Responsible frontier AI research
Key facts
- Founded in 2010
- Headquartered in London, UK
- Part of Google (Alphabet)
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