Akash Vaish is a Senior Software Engineer with nine years of experience building resilient, large-scale systems across cloud and ML-focused teams, currently working on Gemini at DeepMind within Google. He blends SWE and SRE expertise from roles at Google Maps and AWS Lambda to deliver production-grade infrastructure and data pipelines. As a visiting researcher in MIT Media Lab’s Fluid Interfaces group, he developed on-device ML for memory augmentation and personalized learning, demonstrating a strong bridge between research and product engineering. Academically trained in both mathematics (M.Sc. Hons) and computer science (B.E. Hons) at BITS Pilani, he brings rigorous problem-solving and formal reasoning to software design. An active open-source contributor, he enhanced core capabilities in the widely used SymPy CAS—improving number theory, polynomial handling, and periodicity functions—showing attention to correctness in mathematical software. Based in Dublin, he combines deep systems instincts with a knack for machine-learning-enabled user-facing innovations.
9 years of coding experience
3 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science
Contributions:124 commits, 55 PRs, 150 comments in 1 year 4 months
Contributions summary:Akash primarily contributed to the backend of the sympy/sympy repository. Their commits focused on modifying and improving the `ntheory` module, particularly the `totient` function, by allowing it to accept symbols and expressions, and raising exceptions for invalid inputs. They also made changes to the `degree` function in the `polys` module, requiring a specified generator for multivariate expressions. In addition, they implemented support for the modulo operation in the `periodicity` function.
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