5 Odometry Jobs

As a Perception Engineering Intern / Apprentice at 10xConstruction, you will help our autonomous drywall-finishing robots "see" the job-site. You'll design and deploy perception pipelines—camera + LiDAR fusion, deep-learning vision models, and point-cloud geometry—to give the robot the awareness it needs. Key Responsibilities Build ROS 2 nodes for 3-D point-cloud ingestion, filtering, voxelisation and wall-plane extraction (PCL / Open3D) Train and integrate CNN / Transformer models for surface-defect detection and semantic segmentation Implement RANSAC-based pose, plane and key-point estimation; refine with ICP or Kalman/EKF loops Fuse LiDAR, depth camera, IMU and wheel odometry data for robust SLAM and obstacle avoidance Optimise and benchmark models on Jetson-class edge devices with TensorRT / ONNX Runtime Collect, label and augment real & synthetic datasets; automate experiment tracking (Weights & Biases, MLflow) Collaborate with manipulation, navigation and cloud teams to ship end-to-end, production-ready perception stacks Qualifications & Skills Solid grasp of linear algebra, probability and geometry; coursework or projects in CV or robotics perception Proficient in **Python 3.x and C++17/20**; comfortable with git and CI workflows Experience with **ROS 2 (rclcpp / rclpy)** and custom message / launch setups Familiarity with **deep-learning vision** (PyTorch or TensorFlow)—classification, detection or segmentation Hands-on work with **point-cloud processing** (PCL, Open3D); know when to apply voxel grids, KD-trees, RANSAC or ICP Bonus: exposure to camera-LiDAR calibration, or real-time optimisation libraries (Ceres, GTSAM) Why Join Us Work side-by-side with founders and senior engineers to redefine robotics in construction Build tech that replaces dangerous, repetitive wall-finishing labor with intelligent autonomous systems Help shape not just a product, but an entire company—and see your code on real robots at active job-sites Requirements Python 3.x C++17/20 ROS 2 PyTorch Open3D RANSAC

Location: Pune Qualification: Bachelor's degree in Robotics, Computer science, Electrical engineering, or related field. Role Overview: We are seeking a Senior SLAM Engineer to join our core autonomy team. This role will focus on developing and optimizing 3D LiDAR-based SLAM solutions, enabling reliable and accurate localization and mapping for autonomous robots deployed across complex, real-world environments. Preferred Qualifications: Experience with loop closure, global mapping, and multi-session SLAM. Familiarity with PCL, Open3D, or similar libraries for point cloud processing. Contributions to open-source SLAM projects or publications in leading robotics conferences (e.g., ICRA, IROS, RSS). Knowledge of embedded systems and performance optimization on resource- constrained hardware. Experience working with remote or distributed robotics teams. Responsibilities: Develop robust, real-time SLAM systems using 3D LiDARs and other onboard sensors. Design and implement factor graph-based optimization pipelines (e.g., GTSAM, Ceres, iSAM2). Integrate SLAM with IMU, wheel odometry, and vision-based systems for sensor fusion. Continuously test and validate SLAM modules across diverse real-world deployments — including crowded airports, large malls, and hospitals. Collaborate closely with perception, controls, and navigation teams to ensure seamless robot autonomy. Profile and optimize SLAM performance for embedded compute platforms. Contribute to the long-term SLAM roadmap and evaluation infrastructure. Minimum Qualifications: Bachelor’s degree in Robotics, Computer Science, Electrical Engineering, or a related field. 3+ years of hands-on experience developing SLAM systems for autonomous robots. Proven expertise with 3D LiDAR-based SLAM in large, dynamic indoor environments. Strong grasp of probabilistic estimation, sensor fusion, and graph optimization. Proficient in C++ and Python in a Linux-based development environment. Experience with GTSAM, iSAM2, or Ceres Solver. Familiarity with ROS/ROS2 and standard robotics middleware. A track record of deploying SLAM solutions in real-world applications. Job Types: Full-time, Permanent Pay: Up to ₹1,500,000.00 per year Schedule: Day shift Education: Bachelor's (Preferred) Experience: SLAM: 2 years (Required) GTSAM, iSAM2, or Ceres Solver.: 2 years (Required) C++ and Python in a Linux-based development environment.: 2 years (Preferred) Location: Pune, Maharashtra (Required) Work Location: In person

Stride Dynamics We are an early-stage Robotics startup developing autonomous aerial robots. We are IIT Kanpur Alumni with extensive experience building autonomous systems for government, defence and enterprises in India and abroad. With Stride Dynamics, we envision leading the next generation of autonomous aerial robots in India and making global standard products for defence, government and enterprises. The Role We are looking for someone with a passion for working on hardware and autonomous systems. As a robotics engineer, you will work on our core technology for autonomous flight and contribute from conceptualisation to deployment. You will have the opportunity to work on concepts like localisation, controls, perception, navigation, and planning. We are working on developing aerial vehicles with very robust localisation, enabling them to navigate in any conditions (indoors, dark, dusty, high altitude GNSS jamming scenarios, etc.). The Work Design, develop and debug the autonomy software stack for our systems. Work on computer vision, learning based perception, and localisation for aerial systems. A lot of testing in real-world environments. Document and maintain efficient, modular, and reliable C++ code. Develop and improve algorithms for various autonomy modules. Research, understand and implement state-of-the-art methods.. We’re looking for someone with Experience with hardware and implementing algorithms. Experience in C++, Python and ROS. Experience with computer vision, localisation (filtering, PGO, visual odometry). Has Experience with Linux Development Environment and tools like CMake, Git, etc. Bonus if you: Have hands-on experience with robots in the form of projects or competitions. Experience/knowledge of Deep Learning based approaches in Robotics. Experience with GPU/VPU-accelerated programming (eg, CUDA, OpenCL). Published research in the Robotics domain. If you match the above, why us Work in a culture that celebrates innovation, creativity, and the freedom to challenge the status quo. Work with a team of people who are passionate about hardware and robotics. Join us and help us design the future of drones! Apart from the above job description, if you think you can contribute in any other domains (eg, embedded software, hardware, machine learning), feel free to reach out to us. Show more Show less

Job Description We are looking for a passionate and skilled Robotics AI/ML Engineer to join our team in developing intelligent and autonomous drone systems. You will lead the development of drone software stacks, integrating onboard intelligence (AI/ML) with robotic middleware (ROS/ROS2) and backend systems. The ideal candidate has at least 1 year of hands-on experience in building real-world robotics or drone software, with strong command over ROS/ROS2, computer vision, and machine learning applied to autonomous navigation, perception, or decision-making. Key Responsibilities Drone Software Development Build and maintain core ROS/ROS2-based software for autonomous flight, navigation, and perception Develop real-time systems to handle sensor fusion, path planning, obstacle avoidance, and mission execution Implement algorithms for drone localization (GPS, SLAM, visual odometry) and mapping AI/ML Integration Develop and train AI/ML models for perception (e.g., object detection, tracking, segmentation) Deploy and optimize AI models on edge hardware (Jetson, Raspberry Pi, Odroid, etc.) Work on multi-camera vision, lidar fusion, and real-time inference pipelines System Integration & Backend Communication Integrate drone software with backend/cloud systems using ROSBridge, WebSockets, MQTT, or custom APIs Build data pipelines for telemetry, health monitoring, and AI inference output Work with DevOps/Backend teams to ensure smooth interface with mission control and analytics dashboards Testing & Simulation Set up and manage simulated environments (e.g., Gazebo, Ignition) for testing flight logic and AI behavior Conduct real-world test flights with live data and iterative tuning of software models Required Qualifications Bachelor’s or Master’s degree in Robotics , Computer Science , Electrical Engineering , or related field Minimum 1 year experience building autonomous systems using ROS/ROS2 Proficient in Python and C++ with experience writing ROS nodes and launch files Experience deploying AI/ML models for perception or control (e.g., YOLO, DeepSORT, CNNs, LSTMs) Hands-on experience with drones or mobile robotics platforms (simulation or real-world) Comfortable with version control (Git), Linux environments, and debugging complex robotic systems Preferred Skills Experience with drone-specific stacks (PX4, ArduPilot, MAVROS) Experience with edge AI deployment tools (TensorRT, ONNX, OpenVINO) Familiarity with CV frameworks like OpenCV, TensorFlow, PyTorch Experience with cloud platforms for robotics (AWS RoboMaker, Azure, etc.) Understanding of control systems (PID, MPC), SLAM, or multi-agent systems Knowledge of cybersecurity best practices in robotics and IoT Job Types: Full-time, Permanent Pay: ₹180,000.00 - ₹240,000.00 per year Schedule: Day shift Fixed shift Monday to Friday Ability to commute/relocate: Hyderabad, Telangana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Have you ever worked on Drones or built a drone? Experience: Robotics AI / ML: 1 year (Required) License/Certification: AI / ML certification (Preferred) Location: Hyderabad, Telangana (Required) Work Location: In person

At Karman Drones , we’re building the next generation of unmanned aerial vehicles engineered for high-impact missions. We’re looking for a Senior UAV Systems Engineer who thrives in a fast-paced environment and is passionate about solving complex technical challenges across real-time, safety-critical systems. In this role, you’ll work at the intersection of control theory, embedded systems, and aerial vehicle integration—driving innovation across Fixed-Wing, VTOL, and Multirotor UAV platforms. What You’ll Do ● Architect, model, and optimize UAV systems for high-reliability flight operations. ● Lead root cause investigations for aircraft incidents and implement corrective system improvements. ● Integrate, configure, and tune autopilots (PX4, ArduPilot, custom stacks) across diverse airframes. ● Analyze flight logs, telemetry streams, and onboard sensor data to fine-tune flight performance. ● Design and validate system-level avionics including power systems, EMI mitigation, and hardware layout. ● Collaborate with cross-functional teams for mission-specific configurations and payload integration. ● Drive rigorous testing workflows—HIL/SIL simulations, validation protocols, and safety analysis. What You Bring ● Education : B.Tech or M.Tech in Mechatronics, Electronics & Communication, Aerospace Engineering, or related fields. ● Experience : ○ 2+ years of experience with a B.Tech or 1+ year with an M.Tech in UAV system development and integration. ○ Proven expertise in real-time autopilot tuning, control system calibration, and flight logic optimization using PX4, ArduPilot, or proprietary flight stacks. ○ Solid grounding in control theory, sensor fusion (EKF/UKF), PID tuning, and UAV flight dynamics. ○ Strong experience with flight data log analysis tools: Mission Planner, QGroundControl, UAVCAN monitors, uLog/BIN viewers. ○ Familiarity with MAVLink protocol (custom messages, telemetry streaming, mission control, payload management). ○ System-level understanding of UAV architecture: avionics layout, EMI/EMC best practices, power distribution, and vibration mitigation. ○ Practical knowledge of embedded autopilot platforms (e.g., Cube Orange+, Pixhawk series, STM32 boards) and peripheral integration (GNSS, magnetometer, barometer, airspeed sensor, rangefinder). ○ Hands-on experience with SIL/HIL testing for control validation using Gazebo, JSBSim, or similar simulation tools. ○ Proficient with serial bus protocols and RC systems: SBUS, PPM, DSM, CRSF. ○ Demonstrated payload integration (EO/IR gimbals, LiDAR, hyperspectral, SIGINT) and interface development for gimbal control. ○ Familiarity with fail-safe implementations and autonomous recovery (RTL, parachute deployment, geofence management). ○ Awareness of state-of-the-art avionics trends including AES-encrypted RF, FHSS, anti-jam/spoof systems, and secure telemetry systems. Bonus Skills (Preferred) ● Experience with edge computing platforms (NVIDIA Jetson, Raspberry Pi CM4, etc.) for autonomy or perception. ● Familiarity with ROS/ROS2 for mission logic or autonomous flight control. ● Knowledge of GNSS-denied navigation techniques (visual odometry, LiDAR SLAM, inertial-only navigation). ● Awareness of secure communication protocols, anti-jamming/anti-spoofing tech, and EW-resilient system design. ● Hands-on work with SDR-based payloads, RF link analysis, and antenna system integration. Why Join Karman Drones? At Karman Drones, you’ll be working on industry-defining aerial platforms designed for real-world applications in defense, mapping, surveillance, and emergency response . We are a tight-knit, innovation-driven team of engineers, technologists, and visionaries pushing the boundaries of unmanned systems in India. By joining us, you will: Contribute to real-world projects that make a national impact Work on cutting-edge UAV technology , from design to deployment Be part of a team that values innovation, speed, and continuous learning Grow your career in a fast-evolving and mission-focused startup environment How to Apply Click the “Apply Now” button. Or send your resume and relevant documents to careers@karmandrones.com Take your UAV expertise to the next level—and help shape the future of aerial technology with us. Show more Show less