Raveesh Bhalla is a product-focused researcher and builder with 13 years of experience designing AI-driven systems at the intersection of machine learning, product design, and systems thinking. He has led large-scale initiatives at Netflix and LinkedIn—rebuilding homepage recommendations around a shared >1B-parameter foundation model and reframing jobs and recommendations as joint optimization problems that helped scale SMB hiring to over $1B annualized revenue. Earlier-stage roles as Haptik’s first product hire, a founder, and fractional CPO sharpened his 0→1 instincts and practical engineering chops, enabling him to ship ML-infused user experiences from mobile-era constraints to modern LLMs. Currently based in the Bay Area, he researches continual learning and human-feedback mechanisms that let models update behavior without full retraining cycles. Colleagues rely on him to rethink success metrics and incentive structures—moving teams from raw engagement to quality outcomes—and he routinely dives into system-level details to make those changes stick.
Contributions:8 releases, 4 PRs, 15 pushes in 2 years
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