{"id":1250532,"url":"https://alion.io/job/inferigence-quotient-guidance-and-navigation-engineer","title":"Guidance and Navigation Engineer","company":{"id":3800962,"name":"Inferigence Quotient","domain":"inferq.com","url":"https://alion.io/company/inferigence-quotient","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Robotics","role_family":"Robotics","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13500,"max_usd":36000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":149},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Git","optional":false},{"name":"Inertial Navigation","optional":false},{"name":"Linux","optional":false},{"name":"MATLAB","optional":false},{"name":"Python","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"Simulink","optional":false},{"name":"Visual-Inertial Odometry","optional":false},{"name":"ArduPilot","optional":true},{"name":"Ceres Solver","optional":true},{"name":"GTSAM","optional":true},{"name":"ROS","optional":true},{"name":"ROS2","optional":true},{"name":"SLAM","optional":true}],"status":"live","first_seen_at":"2026-09-24T12:37:54Z","employer_posted_date":null,"last_verified_at":"2026-09-24T12:37:54Z","board_verified":false,"closed_at":null,"days_open":37,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":37},"description":"Position: Guidance & Navigation Engineer\nExperience: 1–3 Years\nLocation: Bengaluru, Karnataka\nEmployment Type: Full-time\n\nAbout the Role\nWe 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.\nThe 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.\n\nKey Responsibilities\nDesign, develop, and optimise navigation and guidance algorithms for UAVs.\nDevelop state estimation algorithms using IMU, GNSS, magnetometer, barometer, cameras, LiDAR, radar, and other onboard sensors.\nDesign and implement estimation filters such as: EKF, UKF, Point-mass Filter\nDevelop sensor fusion algorithms for robust localisation under degraded or denied GNSS conditions.\nWork on inertial navigation, dead reckoning, visual-inertial odometry (VIO), visual odometry (VO), and multi-sensor navigation systems.\nDevelop guidance algorithms for waypoint navigation, path following, trajectory generation, and autonomous mission execution.\nPerform simulation, algorithm validation, and performance analysis using MATLAB/Simulink, Python, or C++.\nAnalyse flight logs and sensor data to improve navigation accuracy and system robustness.\nIntegrate navigation software with autopilots, embedded processors, and avionics systems.\nSupport hardware-in-the-loop (HIL), software-in-the-loop (SIL), and field flight testing.\nWork closely with perception, controls, embedded software, and systems engineering teams.\n\nRequired Qualifications\nB.E./B.Tech/M.E./M.Tech in Aerospace Engineering, Robotics, Electronics, Electrical Engineering, Computer Science, Mechatronics, or a related discipline.\n1–3 years of experience in navigation, estimation, robotics, autonomous systems, or UAV development.\nStrong understanding of: Linear Algebra, Probability and Statistics, Estimation Theory, Kinematics, Coordinate Systems, Control Systems,\nExperience developing estimation filters, especially EKF or UKF.\nGood understanding of IMU error modelling and inertial navigation.\nExperience with Camera, IMU Calibration and Synchronisation\nExperience with multi-sensor fusion.\nStrong programming skills in C++ and Python.\nExperience with MATLAB/Simulink for algorithm development and validation.\nFamiliarity with Linux development environments.\nExperience with Git version control.\n\nPreferred Skills\nExperience with Visual-Inertial Odometry (VIO), Visual Odometry (VO), or SLAM with loop closure techniques\nKnowledge of factor graph optimisation (GTSAM, Ceres Solver, g2o, etc.).\nExperience with ROS/ROS2.\nFamiliarity with PX4 or ArduPilot.\nExperience working with embedded Linux or ARM-based processors.\nUnderstanding of UAV flight dynamics and autopilot architectures.\nExperience with flight data analysis and debugging.\nExposure to airborne software development processes and coding standards (e.g., MISRA C++).\n\nPersonal Attributes\nStrong analytical and problem-solving skills.\nAbility to work independently on challenging technical problems.\nGood communication and documentation skills.\nPassion for robotics, autonomous systems, and aerospace technologies.\nWillingness to participate in field trials and flight testing.\n\nThis role offers the opportunity to work on cutting-edge UAV autonomy technologies from algorithm development through real-world flight validation.\nSkills\nVIO, ROS, PX4, Ardupilot, Avionics, gazebo, FlightGear, FlightDynamics","description_format":"text","description_chars":3703,"description_truncated":false,"requirements":{"experience_years_min":1,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T18:00:00Z"}],"visa":[],"liveness":{"score":16,"band":"cold","label":"Long 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