Staff Software Engineer, Machine learning Performance

Requirements:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.

Nice to haves:

• Experience in performance analysis and optimization, including system architecture, performance modeling, or similar.
• Experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience in a technical leadership role leading project teams and setting technical direction.
• Experience in distributed development and large-scale data processing.
• Experience in compiler optimizations or related fields.

What you'll be doing:

• Focus on Large Language Models (Google Deepmind Gemini, Bard, Search Magi, Cloud LLM APIs), performance analysis, and optimizations.
• Identify and maintain Large Language Model (LLM) training and serving benchmarks that are representative to Google production, industry and Machine Learning community, use them to identify performance opportunities and drive TensorFlow/JAX TPU out-of-the-box performance, and to gate TF/JAX releases.
• Engage with Google Product teams to solve their LLM performance problem such as onboarding new LLM models and products on Google new TPU hardware, enabling LLMs to train efficiently on very large-scale (i.e., thousands of TPUs), etc.
• Explore model/data efficiency techniques such as new ML model architecture/optimizer/training technique to solve a ML task more efficiently, new techniques to reduce the label/unlabeled ML data needed to train a model to aim accuracy.

Perks and benefits:

• Advanced technology and tools that help developers build more sustainably.
• Opportunities to switch teams and projects to grow and evolve alongside the business.
• Equal opportunity and affirmative action employer commitment.
• Culture of belonging and providing equal employment opportunity regardless of various factors.
• Global collaboration and communication opportunities.