Aaditya already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
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About
Robotics engineer from UIUC’s Intelligent Motion Lab who led the perception stack for a humanoid robotic nurse, fusing camera/LiDAR/IMU on NVIDIA Jetson Orin for real-time localization and scene understanding across six robots. Deep expertise in ROS 2 and edge ML optimization (TensorRT, CUDA, zero-copy), delivering major latency/throughput gains (10 FPS to 22+ FPS) and building fault-tolerant pipelines with gRPC offloading and real-time reliability practices.
Experience
Lead ML Infrastructure and Fullstack Software EngineerTrvise
Robotics Research InternIntelligent Motion Lab UIUC
Embedded Software Intern, AI InfrastructureSamsara Inc
USA IoT Lab InternTCS
Senior Software Developer / Launch OperationsIllinois Space Society
Education
University of Illinois at Urbana-Champaignbachelor, Computer Science (2026)
Key Strengths
Led development of a multi-sensor perception stack for a humanoid robotic nurse (camera/LiDAR/IMU) across six robots
Solved multi-sensor time synchronization via custom ROS 2 time alignment with jitter buffering to stabilize SLAM
End-to-end edge inference optimization on Jetson Orin (TensorRT FP16, layer fusion, plugins, fused CUDA preprocessing)
Improved throughput from ~10 FPS to 22+ FPS and reduced frame latency ~40% with minimal accuracy loss
Designed low-latency ROS 2 architecture using shared memory, bounded queues, and backpressure to prevent frame drops
Implemented gRPC edge offloading with async streaming, FP16 tensor compression, and failover; reduced p95 latency ~250 ms to ~90 ms
Reduced per-frame latency ~25% and CPU load ~40% using ROS 2 composable nodes with intra-process zero-copy
Production-grade real-time reliability practices: instrumentation, health checks, deterministic scheduling, HIL testing, graceful degradation
Reference Highlights
Strongly Recommended
Incredibly skilled in complex robotics and real-time systems
Deep robotics expertise (taught the reference a lot about robotics)
Built and deployed an AI-driven product end-to-end (backend ownership)
Strong ownership in ambiguous requirements
Able to lead and assign tasks to other team members
Builds efficient and scalable systems; considers tradeoffs