Shashank Shekhar
Research Engineer at Google DeepMind
Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolShashank Shekhar is a research engineer and AI practitioner with 12 years of experience building and deploying machine learning systems across academia, startups, and big tech. He currently works on the Foundational Research Incubation team at Google DeepMind and serves as a technical advisor to the Vector Institute, focusing on LLMs, agents, and data readiness. A founder who bootstrapped Dice Health to profitability and exit, he combines product instincts with deep technical knowledge in large-model training, inference optimization, and evaluation systems. His background includes AI research roles at Meta FAIR, Vector Institute, and the University of Guelph, with publications in computer vision and explainability. He also founded the widely used awesome-mlss repository and newsletter, reflecting a commitment to community knowledge-sharing in ML education. Comfortable shifting between research, advising, and hands-on engineering, he helps teams scale data pipelines and operationalize large-model workflows.
12 years of coding experience
6 years of employment as a software developer
Bachelor of Technology Electronics and Communications Engineering, Bachelor of Technology Electronics and Communications Engineering at Indian Institute of Technology (Indian School of Mines), DhanbadMaster of Applied Science Artificial Intelligence, Master of Applied Science Artificial Intelligence at University of Guelph
Spanish, Hindi, English
Github Skills (152)
plotly-dash10
notebook10
probabilistic-programming10
python10
mcmc10
deep-learning10
bayesian-inference10
flask10
data-exploration10
data-engineering10
data-analytics10
data-viz10
ml10
superset10
neural-network10
Programming languages (9)
Github contributions (5)
shkr/pymc3
Mar 2017 - May 2018
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Contributions:118 pushes, 10 branches in 1 year 1 month
pythontheanomachine-learningprobabilistic-programmingbayesian-statistics
shkr/Optimization-methods
Nov 2013 - Nov 2015
Contributions:7 commits, 1 branch in 2 years
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