Nikhil Suresh is an applied machine learning engineer with nine years of software experience and a Computer Science MS from UCLA, currently building ML products as a Member of Technical Staff at Cohere. He has shipped production ML systems across startups and moonshot teams—helping Rehearsals win enterprise customers through embedding-driven personalization and slashing costs on core AI infrastructure, and contributing to projects at X, NVIDIA, and GetInsured. Comfortable across TensorFlow, PyTorch, and GCP/Vertex AI, he moves seamlessly from research prototypes (predictive wildfire models and gesture-recognition RNNs) to scalable products like Chrome demo extensions and automated Jira ticketing agents. Nikhil’s work blends deep technical rigor with product-minded engineering: he designs embedding platforms and memory features that both improve model quality and drive measurable revenue. Based in New York, he’s drawn to climate, sports analytics, and mathematical problems, and he relishes exploring new frameworks and uncharted ML applications. An early robotics leader and repeat intern at moonshot labs, he brings a rare mix of hands-on embedded, full-stack, and applied-ML experience.
9 years of coding experience
9 years of employment as a software developer
High School Diploma, High School/Secondary Diplomas and Certificates, High School Diploma, High School/Secondary Diplomas and Certificates at Nueva Upper School
Contributions:3 pushes, 1 branch in 2 years 4 months
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Nikhil Suresh - Member Of Technical Staff, Applied ML at Cohere