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Lead AI & Autonomous Systems Engineer Artificial Intelligence | Computer Vision | Robotics | Autonomous Systems Location: Bengaluru, India Experience: 47+ years Company: Tolle Labs Pvt. Ltd. Employment: Full-time About Tolle Labs Tolle Labs is building the intelligence layer for the next generation of autonomous machines. We work at the intersection of Artificial Intelligence, Computer Vision, Robotics, Autonomous Navigation, UAVs, UGVs, intelligent sensing, edge computing and Physical AI. Our objective is to build systems that can see, understand, reason, navigate and act autonomously in complex real-world environments. Our platforms span unmanned aerial vehicles, autonomous ground robots, intelligent surveillance systems and emerging robotic platforms. We are looking for an exceptional AI engineer who wants to move beyond conventional software AI and build intelligence that operates in the physical world. The Role We are looking for a highly capable Lead AI & Autonomous Systems Engineer with strong experience across Computer Vision, Deep Learning, perception, sensor fusion and autonomous systems. This is not simply a Computer Vision Engineer position. We want someone capable of architecting the AI and perception stack of an autonomous machine whether that machine is a drone, UGV, humanoid robot, robotic platform or future autonomous system. You should be comfortable working with data coming from: RGB and low-light cameras Stereo/depth cameras Thermal cameras LiDAR Radar IMUs GPS/GNSS Ultrasonic and proximity sensors Other robotic and environmental sensors Your challenge will be to convert these sensor streams into real-time situational awareness, navigation intelligence and autonomous decision-making. What You Will Build You will design and develop capabilities including: Computer Vision & Visual Intelligence Real-time object detection and classification Multi-object detection and tracking Person and vehicle detection Target recognition and tracking Semantic segmentation Instance segmentation Image classification Pose estimation Activity recognition Feature extraction and matching Optical flow Depth estimation Monocular and stereo vision Scene understanding Terrain classification Change detection Anomaly detection Visual search and re-identification Low-light and degraded-visibility vision Thermal-image analytics Image enhancement and super-resolution Autonomous Navigation & Robotics AI Develop perception and intelligence systems enabling robots to autonomously understand and navigate their environments. Capabilities may include Autonomous waypoint navigation Vision-based navigation Visual odometry Visual-Inertial Odometry SLAM Visual SLAM LiDAR SLAM Localization and mapping GNSS-denied navigation Dynamic obstacle detection Collision avoidance Path planning Motion planning Trajectory prediction Terrain awareness Traversability analysis Landing-zone detection Autonomous precision landing Autonomous docking Follow-me / target-following systems Indoor navigation Outdoor navigation Autonomous exploration Multi-agent navigation Behaviour planning Sensor Fusion & Multimodal Perception Build systems capable of combining information across multiple sensors. Experience or strong knowledge in areas such as: Camera + IMU fusion Camera + LiDAR fusion LiDAR + IMU fusion GPS + IMU fusion Radar-camera fusion Thermal + RGB fusion Depth-camera perception Multi-camera systems Point-cloud processing Sensor calibration State estimation Kalman Filters Extended Kalman Filters Particle Filters Probabilistic sensor fusion The objective is to give autonomous machines a reliable understanding of their position, surroundings and operating environment even when individual sensors become unreliable. LiDAR & 3D Perception Experience with LiDAR and point-cloud processing will be highly valued. Potential responsibilities include 3D object detection Point-cloud segmentation Point-cloud registration LiDAR odometry 3D mapping Terrain reconstruction Obstacle detection Occupancy maps Cost maps 3D scene understanding Sensor-to-sensor calibration Experience with libraries such as PCL, Open3D or equivalent frameworks is desirable. AI / Deep Learning You should have strong practical experience developing, training, optimizing and deploying AI models. Relevant areas include CNNs Vision Transformers Transformers Multimodal AI Representation learning Self-supervised learning Reinforcement Learning Imitation Learning Behaviour learning Foundation models Vision-Language Models Vision-Language-Action models Generative AI Few-shot / zero-shot vision systems Experience adapting modern AI models for real-world robotics applications will be particularly valuable. Edge AI & Real-Time Deployment Our AI doesnt live only in the cloud. It needs to operate inside machines, in real time, often under severe compute
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.