We're Hiring: Reinforcement Learning Engineer
Full time | Core team
LAT Aerospace | Perception & Autonomy
At LAT Aerospace, we’re building India’s first clean-sheet hybrid-electric STOL aircraft and a next-generation autonomy stack powering aircraft for complex missions. Our team is kicking off a new chapter — developing the full flight-control, obstacle-avoidance, GNSS-denied navigation, and swarm-coordination layers that will define LAT’s autonomy architecture.
As an RL Engineer, you will design, train, and deploy policy learning systems that optimize guidance decisions for multi-agent swarms. Your algorithms will directly shape LAT’s next-generation autonomous behaviors.
What you’ll do
Develop reinforcement learning and policy-learning algorithms that improve swarm guidance, collision avoidance, task allocation, and distributed decision-making.
Integrate RL with classical control and planning — combining learned value functions, cost shaping, and residual control to boost agility, robustness, and safety.
Build scalable training pipelines for multi-agent RL using domain randomization, curriculum learning, simulation rollouts, and extensive scenario generation.
Own sim-to-real transfer, ensuring policies trained in simulation generalize to real-world UAV dynamics, uncertainties, and edge-case environments.
Design multi-agent coordination behaviors such as formation flight, coverage, pursuit/avoidance, collaborative mapping, and decentralized cooperation under minimal communication.
Run frequent field tests to evaluate learned policies on actual UAVs, gather flight data, and iterate rapidly.
Develop evaluation frameworks and debugging tools to diagnose RL failures, mode collapse, instability, or unsafe behaviors.
What we're looking for
Strong fundamentals in reinforcement learning, policy optimization (PPO, SAC, TD3), or multi-agent RL.
Experience with robotics autonomy, motion planning, or control systems.
Proficiency in Python with RL libraries (PyTorch, JAX, RLlib, Stable Baselines, CleanRL, etc.).
Hands-on experience with robotics simulation environments — Isaac Lab, Gazebo, MuJoCo, PyBullet, or custom simulators.
Comfort with integrating RL modules into larger autonomy frameworks and evaluating them on real systems.
Why LAT?
Core-team role building the autonomy brain of India’s most ambitious aerospace startup.
Ownership, speed, and the opportunity to define a new class of systems from scratch.
Top Skills
What We Do
Imagine a world where flying is as easy as taking a bus. A world where air travel isn't just for the major cities, but for everyone, everywhere. No more congested hubs, no more wasted hours in security lines—just seamless, affordable, on-demand flights connecting thousands of destinations that the world has ignored for too long.
We are building the future of mass aviation: a network of high-frequency, low-cost, 8 seater, STOL (short take-off and landing), medium-haul aircraft that make every city, every town, and every community accessible—without compromise.
Powered by next-generation aircraft, designed ground-up for efficiency, built for affordability, and future-proofed for autonomy, we are aiming to rewrite the rules of flight.
Our aircraft will take off and land in compact "air-stops" no bigger than a parking lot—no baggage belts, no security bottlenecks—eliminating the need for complex, expensive airport infrastructure that regional air travel simply doesn't require.
No more waiting. No more detours. No more being forced to drive when you should be able to fly. This isn't the impractical supersonic future of aviation as you are made to believe. This is the real future of aviation that our communities need.
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We are hiring
We’re building a next-gen aerospace company — from scratch.
Our Aircraft team is leading the development of our 8-seater hybrid-electric aircraft, spanning design, prototyping, systems integration, testing, and everything in between.
Our GTE team is focused on building a world-class gas turbine engine. We're especially looking for folks with experience in turbines, rotors, control systems, or anything close.
If you want to build something ambitious and enduring, write to us:
[email protected] (for Aircraft)
[email protected] (for GTE)
