Autonomous Navigation Engineer (Motion Planning & Optimization) at The ePlane Company

Chennai, tamil nadu, India -

Full Time

Start Date

Immediate

Expiry Date

23 Jan, 26

Salary

0.0

Posted On

25 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, Motion Planning, Trajectory Optimization, State Estimation, Optimization, Sensor Fusion, Simulation, Testing, Robotics, ROS, Algorithms, Data Structures, Mathematics, Embedded Systems, Control Theory, Python

Industry

Aviation and Aerospace Component Manufacturing

Description

Chart the Course for the Future of Flight Imagine writing the code that teaches an aircraft to think. At The ePlane Company, you won't just be developing algorithms; you'll be creating the "brain" of our electric flying taxi. This is a unique opportunity to solve some of the most challenging problems in robotics and aviation, from planning the perfect flight path through a dynamic urban environment to ensuring millisecond-perfect state estimation. If you're passionate about optimization and want to see your C++ code navigate the skies, this role is for you. About The ePlane Company The ePlane Company is at the forefront of India's urban air mobility revolution. Incubated at IIT Madras, we are a deep-tech startup dedicated to designing and building the world's most compact electric flying taxi. Our mission is to make door-to-door flying a reality, drastically reducing commute times and decongesting our cities for a cleaner, greener future. We're a passionate team of engineers, designers, and visionaries working on cutting-edge technology, and we're looking for brilliant minds to help us take flight. Roles and Responsibilities As an Autonomous Navigation Engineer, you will be a core member of the team responsible for the aircraft's ability to perceive, plan, and act. You will: Design & Develop: Architect and implement state-of-the-art algorithms for motion planning, trajectory optimization, and state estimation for our eVTOL aircraft. Optimize & Implement: Develop robust, efficient, and real-time C++ code using advanced optimization libraries like NLopt or Ceres Solver to solve complex, non-linear problems. Sensor Fusion: Create sophisticated algorithms to produce highly accurate state estimates by combining data from IMUs, GPS, computer vision, and other onboard sensors. Simulation & Testing: Build and utilize high-fidelity simulation environments to rigorously test, validate, and benchmark your algorithms before real-world deployment. Flight Integration: Collaborate closely with the flight controls and hardware teams to integrate, test, and refine navigation software on the actual aircraft. Champion Quality: Maintain the highest standards for code quality, including conducting rigorous code reviews, developing comprehensive unit tests, and producing clear, thorough documentation. Required Qualifications (Must-Haves) Experience: 3+ years of professional experience in robotics, autonomous vehicles, or a related field. Education: Bachelor’s degree in Aerospace Engineering, Robotics, Computer Science, Electrical Engineering, or a related technical field. C++ Expertise: Expert-level proficiency in modern C++ (C++17/20), with a deep understanding of performance tuning, memory management, and low-level system interactions. Data Structures & Algorithms Mastery: A proven mastery of fundamental data structures (e.g., trees, graphs, heaps) and algorithms (e.g., search, sorting, graph traversal), and the ability to apply them to solve complex robotics problems efficiently. Optimization Expertise: Proven, hands-on experience developing and implementing optimization-based solutions using libraries such as NLopt, Ceres Solver, g2o, or similar. Domain Mastery: Deep theoretical knowledge and practical experience in at least one of the following areas: Motion Planning (e.g., RRT*, A*, Lattice Planners, Search-based planning) Trajectory Optimization (e.g., Direct Collocation, Differential Flatness, CHOMP/STOMP) State Estimation (e.g., Kalman Filters - EKF/UKF, Particle Filters, SLAM, VIO) Mathematical Foundations: Rock-solid understanding of mathematics, particularly linear algebra, multivariate calculus, differential equations, probability theory, and optimal control theory. Robotics Framework: Proven hands-on experience with ROS (ROS/ROS2) for developing and deploying robotics applications. Preferred Qualifications (Good-to-Haves) A Master’s degree or Ph.D. in a relevant field focusing on robotics or autonomous navigation. Experience working in a safety-critical industry such as aviation (DO-178C) or automotive (ISO 26262). Experience with modern software development methodologies, including Agile, CI/CD pipelines, and version control (Git). Experience deploying algorithms on embedded systems and working with real-time operating systems (RTOS). Knowledge of control theory (e.g., PID, LQR, Model Predictive Control - MPC). Proficiency in Python for scripting, data analysis, and prototyping. A portfolio of relevant projects (e.g., a GitHub profile showcasing your work). What We Offer The opportunity to work on a groundbreaking product that will redefine urban transportation. A dynamic, fast-paced, and collaborative work environment with a brilliant and passionate team. Competitive salary and benefits. A culture of innovation where your ideas can directly impact the future of flight.

Responsibilities

As an Autonomous Navigation Engineer, you will design and develop algorithms for motion planning and trajectory optimization for electric flying taxis. You will also collaborate with flight controls and hardware teams to integrate and test navigation software on the aircraft.