We're Hiring:
SLAM 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.
The SLAM layer is the backbone of that mission — enabling exact real-time localization, mapping, and relative positioning for single-vehicle and swarm scenarios.
What you'll do
Build real-time SLAM and localization pipelines for UAVs operating in fully or partially GPS-denied environments.
Fuse multiple perception streams — camera (mono/stereo), IMU, lidar, depth sensors, altimeters, and terrain databases — into consistent state estimates.
Develop relative-position estimation for multi-agent systems: identifying, tracking, and localizing other drones in a swarm using visual/lidar cues.
Integrate terrain-relative navigation (TRN) and map-matching algorithms to achieve sub-meter localization accuracy.
Design robust VIO/VSLAM architectures that work in low-light, motion-blur, and feature-poor environments.
Implement and optimize EKF/UKF-based sensor fusion or factor-graph methods for real-time UAV operation.




Build and maintain simulation and evaluation pipelines for validating localization accuracy under varied conditions (urban, rural, low-altitude, high-dynamics).
Iterate through real-world flight testing to refine robustness, latency, and compute performance on embedded hardware.
What we're looking for
Strong background in SLAM, VIO, VSLAM, or multi-sensor fusion for robotics or UAVs.
Proficiency with C++ and/or Python for real-time SLAM and computational geometry.
Hands-on experience with visual SLAM frameworks (ORB-SLAM, VINS-Fusion, OKVIS, ROVIO, Kimera, etc.).
Expertise in state estimation using EKF/UKF, factor graphs (GTSAM, Ceres), or graph-based optimization.
Experience working with camera + IMU fusion, calibration, synchronization, and noise modelling.
Familiarity with lidar processing, scan matching, ICP/NDT, or lidar-inertial fusion pipelines.
Understanding of 3D geometry, reprojection, depth estimation, and perception for robotics.
Knowledge of embedded compute constraints and techniques for optimizing algorithms for real-time deployment.
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.

📌 Slam Engineer (Haryana)
🏢 Important Business
📍 Haryana