Robotics Engineer
Passionate about bridging cutting-edge AI with physical robotic systems to solve real-world challenges. My work revolves around computer vision, autonomous vehicles, mobile robots, real time systems, and distributed autonomous systems, with a focus on creating technologies that enhance human lives.
I am currently on the lookout for Full-time positions starting May 2026. Please feel free to reach out if you think I would be a good fit for your team!
Python, C++, Bash, PowerShell, Azure CLI, LabView, Embedded C, SQL, Matlab
Deep Learning, ViT, YOLO, Detic, SigLIP, FANUC, NVIDIA Jetson, GEM E2, GEM E4, F1 Tenth, UR3e, Reinforcement Learning
PyTorch, OpenCV, ROS, ROS2, ROBO Flow, Gazebo, Gazebo Ign, Open AI, GEM Stack, Unity, Anaconda, Docker, Azure, Linux
Designing a ROS 2 based automation pipeline hosted in Docker Container for grain quality inspection, integrating multi-sensor systems with existing grain probe infrastructure improving speed, cost, accuracy, hours of operation and safety compared to manual operation of the probe.
Developed a package validation system using a lightweight instance segmentation model, capable of verifying product presence every 30 ms on an edge device, with seamless integration into the defect inspection pipeline.
Analyzed and trained SOTA pose detection models on homogeneous vs. heterogeneous environment swine datasets to evaluate their effectiveness at keypoint detection in real-world farm settings, contributing to an upcoming research publication.
Optimized multimodal deep learning pipeline for STRETCH Robot AI, enabling compatibility with low-end GPUs by reducing VRAM usage from 12GB to 7GB .
Improved the reliability and safety of elderly-assistive object pick-and-place tasks, doubling the pickup success rate from 20% to 40%.
My course work includes working with mobile robotics and autonomous vehicles, currently focusing on developing my skill set on optimizing deep learning perception models and real time systems coordination.
Related Course Work: Autonomous Vehicle System Engineering, Deep Learning with Computer Vision, Principles of Safe Autonomy
Implemented CI/CD pipelines for provisioning and managing Docker Containers, Azure Cloud and BareMetal servers, reducing manual setup and maintenance effort by up to 60%.
Evaluated cognitive vision models on IoT edge servers to assess their accuracy in detecting and reporting faulty surveillance cameras at Microsoft data centers.
Developed an IoT device to detect obstacles blocking accessibility of fire extinguishers and alert security in realtime for Nokia’s Manufacturing Factory as part of their safety measures.
My course work included working with embedded systems, real time system processing and image processing
Related Course Work: Real Time Embedded Systems, Image Processing,
My projects revolve around developing systems that combine the precision of robotics with the adapatability of AI, enabling smarter homes, safer autonomous vehicles, and tools that amplify human potential.
nvikramraj1305@gmail.com