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Vetted Object Detection Professionals
Pre-screened and vetted.
SHREYA SINHA
Intern Robotics Engineer specializing in autonomous systems and perception
“Robotics software candidate with hands-on ROS2 experience building an autonomous UR7e cake-decorating robot, owning trajectory planning from perception-driven design selection through IK-based waypoint execution. Also optimized a depth-camera object-detection system for assistive glasses (doubling FPS from ~5 to ~10) and is currently exploring distributed Raspberry Pi robot networking to emulate satellite-style handoffs.”
Shardul Jeurkar
Intern Applied AI/Software Engineer specializing in computer vision and full-stack platforms
“Built production LLM systems focused on reliability and safety, including a plain-English deployment tool that generates validated plans and provisions to Kubernetes while preventing unsafe actions via schema enforcement and plan/execute separation. Also created multi-LLM workflows (LangGraph) and stakeholder-friendly demos at Bosch, including a PyQt/FastAPI/CUDA app comparing SAM2 vs SAMWISE for on-device object detection with intuitive UX for business users.”
Principal Autonomy Engineer specializing in robotics, perception, and localization
Junior Software Engineer specializing in ML, computer vision, and data engineering
Junior Robotics & AI Researcher specializing in safe reinforcement learning and generative models
Mid-level Robotics Engineer specializing in autonomy, computer vision, and reinforcement learning
Intern Machine Vision & Robotics Engineer specializing in computer vision and reinforcement learning
Entry-level Robotics Engineer specializing in reinforcement learning and autonomous systems
Senior AI/ML Engineer specializing in Computer Vision, NLP, and Generative AI
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Intern Machine Learning Engineer specializing in RL post-training for LLMs and VLMs
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Kanishka Harwani
Intern Robotics & Embedded Systems Engineer specializing in ROS2 autonomous mobile robots
“Recent graduate with a prototyping/hardware engineering background who is building a ROS2-dependent swarm robotics system for transporting non-standard cargo using 3+ robots. Has hands-on experience integrating multiple sensor modalities (LiDAR, IMU, GPS, radar) and developing custom teleoperation ROS nodes, currently tackling networking/communication challenges in multi-robot coordination.”
Abhishek Patil
Senior Robotics Researcher specializing in SLAM and 3D computer vision
“Robotics software engineer (10+ years ROS/ROS 2) currently leading the perception stack for Omron’s AMR fleet, including a scalable factory SLAM system that combines vision with laser SLAM to handle corridor aliasing. Strong in real-time embedded optimization on NVIDIA Jetson (CUDA + profiling) and fleet-scale validation via multi-robot Isaac Sim scenarios (USD-to-ROS 2 bridging, Nav2 in crowded scenes). Also contributed to a cloud-native reality-capture/3D reconstruction pipeline at Hilti using Docker and Kubernetes.”
Joseph Rivas
Senior AI/ML Engineer specializing in GenAI, MLOps, and computer vision
“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”
Robert Zhu
Mid-level Robotics & Systems Engineer specializing in GPU virtualization and autonomous manipulation
“Robotics software engineer focused on vision-guided manipulation with a Franka Emika Panda on ROS 2, using an RGB-D camera and a trained YOLO-OBB detector to estimate 3D object poses for pick-and-place. Strong in perception-to-planning integration (TF2 alignment, message synchronization, MoveIt 2) and in debugging sim-to-real issues, including symmetry-aware orientation handling and grasp repeatability tuning.”
Rojin Bakhti
Junior Software Engineer specializing in Edge AI and ML deployment
“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”
Hitesh Bhojwani
Mid-level Robotics Software Engineer specializing in SLAM and 3D computer vision
“Robotics software engineer focused on outdoor mobile robot localization and navigation, building ROS1/ROS2 systems with NavSat+EKF sensor fusion and custom Nav2/Costmap2D extensions for 3D obstacle clearance. Demonstrates strong real-world troubleshooting by tracing localization drift to a failing IMU connector, repairing it, and then creating sensor-health monitoring tooling; experienced taking features from Gazebo simulation through field testing to Docker/Kubernetes deployment with CI via GitHub Actions.”
Mayuna Gupta
Senior Data Scientist specializing in computer vision and medical imaging
“Built and deployed an LLM-powered RAG system (PubChemRAG) for a 4D Mitospace project to compare mechanisms across a ~100-drug glossary and surface expected pathway/phenotypic differences in mitochondrial imaging. Worked closely with biochemistry and microscopy experts to design tiered evaluation benchmarks, iterating on prompts, retrieval quality (corpus hygiene, chunking strategy), and model outputs under GPU constraints using LangChain.”
Vishnu Mukundan Thanikunathe Manoj
Junior AI/ML Engineer specializing in LLM agents, explainable AI, and computer vision
“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”
Matthew Frank
Senior Machine Learning Engineer specializing in computer vision and LLM-powered analytics
“Machine learning engineer and startup veteran building InfraSketch (infrasketch.net), a full-stack system-design/diagramming product where users describe systems in plain English and an LLM agent generates and iterates on infrastructure graphs and exports design docs. Owns the entire stack (React/TS + FastAPI/Node, DynamoDB/Postgres, AWS serverless) and focuses on LLM consistency, modular agent architecture, and production-style CI/CD and reliability patterns.”