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.

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.
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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.

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About Inferigence Quotient

Founded :

2017

Type :

Products & Services

Size :

20-100

Stage :

Bootstrapped

About

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

Dr Neeta Trivedi

Connect

Company social profiles

N/A

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