Vinitra Muralikrishnan is a Machine Learning Engineer based in California with nine years of engineering experience, combining four years as a full-stack engineer at Microsoft with two years of hands-on ML, computer vision, and NLP work. She has designed simulation-based inference, causal benchmarking, and LLM-driven dataset generation pipelines for RAG evaluation, and currently accelerates generative AI inference on d-Matrix’s Corsair platform. Proficient across the ML and web stack — Python, PyTorch, LangChain, FastAPI, MLFlow, Docker, Azure ML, and modern front-end frameworks — she bridges research and production to deliver end-to-end systems. Her academic work at UMass Amherst includes causal inference research and creating high-quality financial QA benchmarks using Qwen 32B and LLaMA 70B, reflecting a knack for marrying rigorous methodology with practical engineering. Avid about tooling and reproducibility, she emphasizes evaluation-first dataset generation and inference efficiency rather than model-only improvements.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 3.2, Bachelor of Engineering - BE, Computer Science, 3.2 at KJ Somaiya College of Engineering, Vidyavihar
Master of Science - MS, Computer Science, 3.87, Master of Science - MS, Computer Science, 3.87 at Manning College of Information and Computer Sciences, UMass Amherst
Mathematics and Computer Science, Mathematics and Computer Science at K J Somaiya College of Science and Commerce
Contributions:61 commits, 50 pushes, 1 branch in 1 month
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Vinitra Muralikrishnan - Machine Learning Engineer at d-Matrix