Vikash Balasubramanian
Principal Machine Learning Engineer at Workday
Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolVikash Balasubramanian is a Principal Machine Learning Engineer with 11 years of experience building production AI systems that blend LLMs, agentic orchestration, and large-scale retrieval architectures. He designs end-to-end AI platforms—from model training and evaluation to scalable cloud deployments—specializing in RAG, semantic search, and observability for real-world applications. Vikash has progressed from academic research at the University of Waterloo to senior applied scientist roles at Alexi and now leads ML efforts at Workday, bringing a strong grounding in PyTorch, LangChain, and transformer-based systems. He pairs research-informed techniques (disentangled representations and proximity-based methods from earlier internships) with pragmatic engineering to ship reliable, agentic AI services. An active open-source contributor, he’s fixed race conditions and added language support in the popular Doom Emacs framework, reflecting a hands-on, full-stack problem-solving mindset. Based in Toronto, he combines deep NLP expertise with platform engineering to turn complex research ideas into scalable production features.
10 years of coding experience
10 years of employment as a software developer
Indian Institute of Technology, GuwahatiKendriya Vidyalaya MeenambakkamMaster's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at University of Waterloo
Stackoverflow
3,051reputation
262kreached
26answers
93questions
Github Skills (16)
emacs10
emacs-lisp10
jsonnet9
racket9
debug9
debugging9
devil8
pip6
pandas6
data-structures6
conda6
fastapi6
python6
scikit-learn6
uvicorn6
Programming languages (18)
Github contributions (5)
doomemacs/doomemacs
Jan 2018 - Nov 2019
An Emacs framework for the stubborn martian hacker
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:7 commits, 6 PRs, 53 comments in 1 year 10 months
Contributions summary:Vikash contributed to the Doom Emacs framework by fixing bugs and adding support for new features. They addressed race conditions in the syntax checking module and resolved a main loading point issue in the ESS package. The user also integrated support for Jsonnet and Racket. Furthermore, the user updated and fixed debugger configurations.
vimemacs-configurationmartianemacsemacs-lsp
vikigenius/conditional_text_generation
Jul 2019 - Nov 2020
Adversarial Latent Space model for dialog generation
Contributions:3 reviews, 36 commits, 2 PRs in 1 year 4 months
pytorchdialoglatent-spacedeep-learningadversarial
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