Summary
Animesh Mishra is a Developer Technology Engineer blending deep-learning research with production-grade distributed systems, currently at NVIDIA after earning an MS in Computer Science from NYU with an AI focus. Over ~9 years of industry and research experience, he has built scalable ETL pipelines, fine-tuned transformer models for healthcare at NYU Langone, and improved cloud storage reliability during a Microsoft stint. He’s strong in HPC and model serving—optimizing CUDA, Flash Attention, TensorRT, and Kubernetes workflows—to push low-latency, GPU-accelerated ML into production. His work spans end-to-end stacks from ROS2-driven robotics data collection to RAG-based policy pipelines, demonstrating an unusual mix of hands-on ML engineering and systems reliability. A repeat hackathon winner and educator, he often pairs experimental model techniques (e.g., diffusion-based denoising and LoRA fine-tuning) with pragmatic CI/CD and monitoring to reduce deployment friction. Based in New York, he thrives on cross-disciplinary projects that move research ideas into scalable, real-world applications.
9 years of coding experience
1 year of employment as a software developer
Masters of Science, Computer Science, 4.0, Masters of Science, Computer Science, 4.0 at NYU Courant Institute of Mathematical Sciences
Computer Engineering, Computer Engineering at Loyola School Jamshedpur
Bachelor of Technology - BTech, Computer Science, 8.64, Bachelor of Technology - BTech, Computer Science, 8.64 at Birla Institute of Technology, Mesra
English, Hindi, Bengali