Description
Key Responsibilities
Own client engagements end to end — technical discovery, solution architecture, hands-on build, and delivery — acting as the technical authority on feasibility.
Translate ambiguous real-world problems into concrete perception and robotics ML architectures; lead demos and proof-of-concept scoping.
Design and build CV and perception systems — detection, segmentation, pose estimation — on the 3D geometry underneath (SE(3), camera models, projection, coordinate frames).
Own sensor calibration and fusion — intrinsic/extrinsic, hand-eye, and LiDAR–camera — plus LiDAR processing (registration, ground segmentation, object detection).
Design egocentric data collection pipelines using wrist/head-mounted cameras, depth sensors, and IMU for robot learning.
Bridge simulation and deployment via domain randomisation, sim setup, and sim-to-real gap analysis.
Evaluate, select, and integrate VLA models, and fine-tune large pretrained models under data and compute constraints.
Build supporting services — agentic loops, REST/gRPC APIs,



and PostgreSQL — to expose model inference and robotics services.
Mentor engineers, drive principled decisions (diagnose before solving), and translate current research into practical client implications.

Required Qualifications
4+ years in robotics ML, computer vision, or technical solutions engineering.
Robust CV and perception — detection, segmentation, pose estimation, optical flow.
Solid 3D geometry — SE(3) transformations, camera models, projection, coordinate frames.
Sensor calibration — intrinsic/extrinsic, hand-eye, and multi-modal alignment.
LiDAR processing and sensor fusion, including LiDAR–camera calibration.
Sim-to-real experience — domain randomisation and sim settings (Isaac Sim, MuJoCo, Gazebo, or Unity Robotics Hub).
Conceptual grasp of VLA architectures and the current SOTA landscape.
Robust Python (PyTorch); able to read and implement research papers.
Prior clie

📌 Ai Senior Engineer Bengaluru
🏢 TELUS Digital
📍 Bengaluru