Lavi Shpigelman
Sr Staff Machine Learning Researcher @Ocado Technology
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WORK HISTORY
Sr Staff Machine Learning Researcher @Ocado Technology
Toronto, ON, CA
Advancing ML across perception, control, and experimentation. Delivering on-robot perception services, closed-loop learning (human-in-the-loop RL / diffusion policy / ACT), and the monitoring - labeling - retraining - A/B testing mlops infrastructure needed to keep models reliable at scale. Advised on and contributed to a video-based real-time double-pick detection service for on-device inference on deployed robotic units using TensorRT; designed an event-based simulation to optimize the precision/recall tradeoff, achieving 80% recall with minimal throughput impact. Created a continual labeling system linking production performance monitoring to automated model retraining tackling distribution drift. Championed redesign of A/B testing infrastructure for no-code production experiments. Developed a statistical model over VLM-based SKU clustering to estimate the SKU pickability range for a new gripper. Researched human-in-the-loop RL to improve chunking imitation learning models (diffusion policy, ACT) for robotic control. Built an academic papers browsing tool utilizing an LLM-based agentic workflow (semantic search, app + MCP service) targeted at conference-goers. Mentored interns; supported cross-team adoption of ML tooling.
EDUCATION
The Hebrew University of Jerusalem
PhD, Computational Neuroscience
Technion - Israel Institute of Technology
Bachelor's degree, Computer Science
SKILLS
ABOUT LAVI SHPIGELMAN
ML Researcher / Engineer with deep experience applying machine learning in robotics, vision, healthcare, and neuroscience.Delivered Multi-modal ML components (for SKU verification, segmentation, tracking, grasping, mishap detection) across four robotic products, some with several hundreds of deployments in multiple sites. Drove cloud MLOps adoption, and scaled ML solutions. Experience in leading research initiatives and collaboration with cross-functional teams to translate technical innovations into useful product components. Believes in “Fall in love with the problem, not the solution” but enjoys when the solution is cutting edge research. Takes pride in empowering colleagues and working collaboratively.
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