NAGARJUN – Robotics & MACHINE LEARNING ENGINEER | COMPUTER VISION | GENERATIVE AI | PYTORCH | AWS – 5+ years Exp Local to Bay Area

NAGARJUN – Robotics & ML Engineer – Ex. Toyota Research Institute – 5+ years Exp – H1B – Local to Bay Area

Consultant's Details: 

Consultant Name: Nagarjun

Current Location: Bay Area,CA

Employer Details:

Employer:Nextgen Technologies Inc

Contact Person:Kushal

Email:kushal.desai@nextgentechinc.com

Note: Please call between 09:30 AM PST to 06:00 PM PST

Phone: +1 (413) 424-0484

NAGARJUN 's Resume

MACHINE LEARNING ENGINEER | COMPUTER VISION | GENERATIVE AI | PYTORCH | AWS

 

PROFESSIONAL SUMMARY

• Machine Learning Engineer with 5+ years of experience building and deploying AI/ML solutions across computer vision, autonomous systems, and robotics domains.
• Strong expertise in deep learning, model evaluation, and large-scale data pipelines using PyTorch and TensorFlow.
• Proven experience in developing production-grade ML pipelines, optimizing model performance, and working with cloud and MLOps tools.
• Hands-on experience with Generative AI, LLMs, and Hugging Face frameworks, including chatbot development and model inference pipelines.
• Adept at solving complex real-world problems and collaborating across cross-functional teams in fast-paced environments.

 

CORE SKILLS

Machine Learning & AI:
Deep Learning, Computer Vision, NLP, Generative AI, LLMs, Model Evaluation, Transfer Learning

Frameworks & Libraries:
PyTorch, TensorFlow, OpenCV, TensorRT, ONNX, Hugging Face Transformers

Programming:
Python, C++, MATLAB, Bash, SQL

Cloud & MLOps:
AWS, Docker, CI/CD (Git), Model Deployment, GitHub Actions

Robotics & Simulation:
ROS/ROS2, SLAM, Motion Planning, Sensor Fusion, Gazebo, CARLA, IsaacSim

Tools & Platforms:
Linux, Git, WandB, gRPC, CUDA

PROFESSIONAL EXPERIENCE

Senior Machine Learning Engineer | Toyota Research Institute (Contract)

Los Altos, CA                                                                                                                    Sep 2025 – Present

• Developed scalable ML evaluation pipelines for autonomous driving systems using Waymo and NavSim datasets.
• Built automated inference and tracking pipelines integrated with CI/CD workflows for model validation.
• Implemented ONNX-based model deployment and inference tracking using Git-based versioning.
• Designed panoramic image stitching system using feature matching and geometric transformations.
• Developed evaluation harnesses for vision-language-action (VLA) models across simulation environments.
• Contributed to development of internal GenAI chatbot leveraging LLMs and Hugging Face frameworks.
• Integrated experiment tracking tools (WandB) and optimized logging for large-scale ML workflows.

 

Robotics & Machine Learning Engineer | Neuro42

Bay Area, CA                                                                                                       Oct 2023 – Sep 2025

• Led development of AI-driven surgical robotic systems integrating ML, computer vision, and control systems.
• Built 3D medical image analysis pipelines using deep learning (3D U-Net) for tumor detection and classification.
• Developed real-time simulation and visualization tools using OpenGL and Python.
• Designed motion planning and trajectory optimization algorithms for robotic automation.
• Implemented anomaly detection models and image reconstruction techniques for MRI data.
• Collaborated across software, electrical, and mechanical teams to deliver production-grade robotic solutions.

 

Perception Engineer | Forterra

MD,USA                                                                                                                               Feb 2022 – Oct 2023

• Developed sensor fusion pipelines combining LiDAR, camera, and radar data using EKF and CV algorithms.
• Built multi-object tracking and localization systems for autonomous vehicle platforms.
• Implemented camera calibration and image processing pipelines using OpenCV.
• Designed data collection, preprocessing, and evaluation pipelines deployed on AWS.
• Optimized real-time perception systems on embedded platforms (NVIDIA Jetson).
• Applied deep learning techniques for obstacle detection and semantic segmentation.

 

ADAS Simulation Engineer | Forterra

MD, USA                                                                                                                              Feb 2022 – Jul 2022

• Built simulation environments using CARLA and ROS for autonomous driving validation.
• Developed synthetic datasets and testing pipelines for perception and planning systems.
• Integrated LiDAR and camera sensor models into simulation frameworks.

 

Motion Planning Engineer | Thordrive

OH, USA                                                                                                                              Sep 2021 – Feb 2022

• Developed route planning and trajectory optimization algorithms for autonomous vehicles.
• Implemented path planning techniques (A*, Dijkstra, Hybrid-A*) for real-time navigation.
• Collaborated with controls teams to optimize vehicle performance and stability.

 

Robotics Navigation Intern | Midea Group

Bay Area, CA                                                                                                                     Jul 2021 – Sep 2021

• Built end-to-end computer vision pipelines for object detection using TensorFlow.
• Trained and deployed models on edge devices (Raspberry Pi, Google Coral TPU).
• Developed evaluation metrics (mAP, precision, recall) for model performance.

 

KEY PROJECTS

Generative AI Chatbot & LLM Integration

• Built internal chatbot leveraging LLMs and Hugging Face models for enterprise applications.
• Designed inference pipelines and prompt-based interactions for AI-driven workflows.

3D Object Detection & Autonomous Driving

• Developed deep learning models for object detection using KITTI dataset.
• Improved inference performance and accuracy using optimized architectures.

Sensor Fusion & Localization System

• Implemented fusion of LiDAR, camera, and IMU data for real-time localization.
• Applied EKF and probabilistic methods for robust tracking.

Medical Image Analysis (3D Deep Learning)

• Built 3D U-Net models for tumor detection and classification in MRI data.
• Improved detection accuracy and processing efficiency.

 

 

EDUCATION

Master’s in Robotics Engineering                                                                                                      2021
Worcester Polytechnic Institute, MA, USA | GPA: 4.0/4.0

Bachelor’s in Mechanical Engineering                                                                                           2019
VIT University, India | GPA: 3.84/4.0

 

ADDITIONAL INFORMATION

• Experience working with large-scale datasets (Waymo, KITTI, COCO)
• Strong background in distributed systems and real-time ML applications
• Publication in IJMET and research contributions in robotics and AI
• Open to Machine Learning Engineer, AI Engineer, and Computer Vision roles