Inferigence Quotient
https://inferq.comAbout
Deep Tech Startup Focusing on Autonomy and Intelligence for Unmanned Systems. Guidance and Navigation, AI-ML, Computer Vision, Information Fusion, LLMs, Generative AI, Remote Sensing
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Jobs at Inferigence Quotient
At InferQ, we are building solutions for autonomous and intelligent aerial systems. We seek a Robotic Navigation Engineer with deep technical rigor and a passion for developing mission-critical navigation, estimation, and path planning systems for UAVs. The role demands hands-on engagement across the autonomy stack. You will work at the intersection of robotics, AI, and aerospace, translating research into reliable field-deployable systems.
Key Responsibilities
- Architect and implement algorithms for joint state estimation, integrating multi-sensor inputs.
- Develop dynamic and real-time path planning solutions for UAVs.
- Create and validate flight simulations using various COTS Simulators or custom HIL/SIL test environments.
- Design and integrate advanced navigation systems.
- Work with avionics, AI, and controls teams to integrate autonomy modules on flight computers and mission systems.
- Conduct flight trials, performance evaluation, and algorithm optimization under real mission conditions.
- Support development of mission-critical autonomy frameworks for UAV systems.
Skillset/ Experience Required
- Strong foundation in linear and nonlinear state estimation and multi-sensor fusion.
- Expertise in path planning and trajectory optimization for aerial platforms.
- Proficiency in C++ / Python and ROS / ROS2 for robotic system development.
- Experience with aerospace kinematics and dynamics modeling, flight control integration, and navigation system design.
- Hands-on experience with Gazebo / X-Plane / AirSim / Unreal Engine simulators.
- Practical understanding of vision-based SLAM, visual odometry, and obstacle avoidance.
- Strong analytical and debugging skills, with a systems-engineering mindset.
- Exposure to AI-based perception systems.
- Integration of algorithms with embedded flight computers.
- Experience with HIL/SIL test setups and flight telemetry systems.
- Familiarity with DO-178C, DO-254, or other lifecycle processes is a plus.
Educational Qualification
- B.E. / B.Tech / M.Tech / Ph.D. in Aerospace, Robotics, Computer Science, Electrical, or related disciplines.
- Academic or project focus in Autonomous Systems, Estimation, Navigation, or AI-based Robotics is preferred.
Position: Guidance & Navigation Engineer
Experience: 1–3 Years
Location: Bengaluru, Karnataka
Employment Type: Full-time
About the Role
We are seeking a highly motivated Guidance and Navigation Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating state estimation, navigation, and guidance algorithms for autonomous UAVs operating in both GNSS-available and GNSS-denied environments.
The ideal candidate should have a strong foundation in estimation theory, sensor fusion, and navigation algorithms, along with hands-on experience in implementing these algorithms on embedded or real-time systems.
Key Responsibilities
- Design, develop, and optimise navigation and guidance algorithms for UAVs.
- Develop state estimation algorithms using IMU, GNSS, magnetometer, barometer, cameras, LiDAR, radar, and other onboard sensors.
- Design and implement estimation filters such as: EKF, UKF, Point-mass Filter
- Develop sensor fusion algorithms for robust localisation under degraded or denied GNSS conditions.
- Work on inertial navigation, dead reckoning, visual-inertial odometry (VIO), visual odometry (VO), and multi-sensor navigation systems.
- Develop guidance algorithms for waypoint navigation, path following, trajectory generation, and autonomous mission execution.
- Perform simulation, algorithm validation, and performance analysis using MATLAB/Simulink, Python, or C++.
- Analyse flight logs and sensor data to improve navigation accuracy and system robustness.
- Integrate navigation software with autopilots, embedded processors, and avionics systems.
- Support hardware-in-the-loop (HIL), software-in-the-loop (SIL), and field flight testing.
- Work closely with perception, controls, embedded software, and systems engineering teams.
Required Qualifications
- B.E./B.Tech/M.E./M.Tech in Aerospace Engineering, Robotics, Electronics, Electrical Engineering, Computer Science, Mechatronics, or a related discipline.
- 1–3 years of experience in navigation, estimation, robotics, autonomous systems, or UAV development.
- Strong understanding of: Linear Algebra, Probability and Statistics, Estimation Theory, Kinematics, Coordinate Systems, Control Systems,
- Experience developing estimation filters, especially EKF or UKF.
- Good understanding of IMU error modelling and inertial navigation.
- Experience with Camera, IMU Calibration and Synchronisation
- Experience with multi-sensor fusion.
- Strong programming skills in C++ and Python.
- Experience with MATLAB/Simulink for algorithm development and validation.
- Familiarity with Linux development environments.
- Experience with Git version control.
Preferred Skills
- Experience with Visual-Inertial Odometry (VIO), Visual Odometry (VO), or SLAM with loop closure techniques
- Knowledge of factor graph optimisation (GTSAM, Ceres Solver, g2o, etc.).
- Experience with ROS/ROS2.
- Familiarity with PX4 or ArduPilot.
- Experience working with embedded Linux or ARM-based processors.
- Understanding of UAV flight dynamics and autopilot architectures.
- Experience with flight data analysis and debugging.
- Exposure to airborne software development processes and coding standards (e.g., MISRA C++).
Personal Attributes
- Strong analytical and problem-solving skills.
- Ability to work independently on challenging technical problems.
- Good communication and documentation skills.
- Passion for robotics, autonomous systems, and aerospace technologies.
- Willingness to participate in field trials and flight testing.
This role offers the opportunity to work on cutting-edge UAV autonomy technologies from algorithm development through real-world flight validation.
Python
Deep Learning
Machine Learning (ML)
C++AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.
Implementation and testing of advanced computer vision algorithms.
Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.
Detailed analysis of results. Documentation, version control, client support, upgrades.
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