Raj Singh is a Senior AI Engineer with 8 years of experience building multimodal ML systems and production pipelines for large consumer platforms. He has driven GenAI safety and real-time inference at Snap, scaled billion‑video training pipelines and deployed latency-sensitive LLMs for 15M+ users, and built text-to-image search and retrieval pipelines at Amazon that materially improved ranking and relevance. Comfortable across research, infra, and product, Raj designs distributed training and inference (PyTorch, HuggingFace, Ray, Kubernetes, AWS) and has a track record of cutting prelaunch testing and data turnaround from months to hours. He was the first ML hire at an AI coaching startup where he shipped transformer-based empathy and sentiment models, showing a knack for product-focused model interpretability. Based in New York and currently at LinkedIn on Member Understanding, Raj combines hands-on engineering with cross-functional leadership and a persistent focus on evaluation and data quality. An unexpected strength: he repeatedly translates complex ML advances into operational speedups and tighter safety baselines that directly accelerate product launches.
7 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.S.) Computer Science and Mathematics, Bachelor of Science (B.S.) Computer Science and Mathematics at Vanderbilt University
Contributions:16 commits, 16 pushes, 1 branch in 4 months
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