Senior Software Engineer, ML Performance, GenAI
Google DeepMind · Mountain View, CA, USA
Frontier labonsitesenior$174k–$252k
At a glance
Highlights
- Drive down cost per token of Gemini inference at scale.
- Bring Gemini to new TPU generations and shape hardware roadmaps.
- Build agentic workflows that discover performance improvements automatically.
What they offer
- 15% bonus target
- equity
- benefits
Ideal candidate
Systems-minded engineer passionate about squeezing maximum performance from large-scale AI workloads and shaping next-gen accelerators through deep optimization and cross-team collaboration.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, Mathematics, or related STEM field or equivalent practical experience
- 5 years of experience in software development, systems programming, or applied ML engineering
- 3 years of experience with performance optimization, systems data analysis, visualization tools, or debugging
- 3 years of experience with Generative AI, Large Language Models, Machine Learning and related frameworks
- 1 year of experience designing and launching production software products or foundation AI systems
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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