Summary
Gopal Krishna is a Machine Learning Engineer with nine years of hands-on experience, currently advancing recommendation and perception systems at Spotify while completing an MS in Computer Science at Northeastern. He specializes in deep learning, reinforcement learning, and computer vision, with practical experience deploying scalable ML services using PyTorch/TensorFlow, FastAPI, Docker, Kubernetes and AWS. His work includes building RL-based ranking models for production recommendation, domain-adaptive medical imaging pipelines, and latency-optimized vision APIs, reflecting a balance of research rigor and production engineering. As a TA and instructor he has mentored large cohorts in computer vision and pattern recognition, and often pairs algorithmic innovation with careful systems design to ship measurable improvements. Notably, he blends simulator-driven offline RL with custom reward engineering to improve real-world streaming metrics—showing a knack for translating complex models into business impact.
9 years of coding experience
4 years of employment as a software developer
Nanodegree, Deep Reinforcement Learning, Nanodegree, Deep Reinforcement Learning at Udacity
Master of Science - MS, Computer Science, Current GPA: 3.95 / 4.0, Master of Science - MS, Computer Science, Current GPA: 3.95 / 4.0 at Northeastern University
Bachelor’s Degree, Computer Science And Engineering, GPA: 8.23/10.0, Bachelor’s Degree, Computer Science And Engineering, GPA: 8.23/10.0 at Jalpaiguri Government Engineering College
English, Hindi