Lead Perception Engineer

Deservely Technologies

Bengaluru

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

Deservely Technologies in Bengaluru, India, is seeking an experienced robotics software engineer to build and optimize 3D perception systems for robots operating in real-world environments. You will develop robust perception pipelines, enabling accurate scene understanding, localization, and decision-making across simulation and real-world sites.

You will prototype and deploy algorithms using LiDAR, IMU, stereo, and RGB cameras, while advancing deep learning models for semantic understanding and

Qualifications

  • 5+ years of experience in 3D perception or robotics.
  • Strong fundamentals in computer vision and 3D perception.
  • Proficient in C and Python; familiar with PyTorch/TensorRT.
  • Experience with SLAM, localization, and multi-sensor fusion.
  • Experience working with real-world data and debugging complex systems.

Responsibilities

  • Design, implement, and deploy realtime 3D perception pipelines using LiDAR, IMU, stereo and RGB cameras.
  • Develop algorithms for spatial/temporal data interpretation for semantic scene understanding.
  • Optimize ego-motion estimation and localization for downstream planning and control.
  • Train and integrate deep learning models for semantic understanding and QA.
  • Automate data collection, training pipelines, and experiment tracking.
  • Benchmark and optimize models for edge devices in resource-constrained environments.
  • Collaborate with Navigation, Manipulation, and Cloud teams for system integration.

Skills

3D Perception
C
Python
PyTorch
SLAM
TensorRT
ROS/ROS2
OpenCV
PCL
Localization

Tools

NVIDIA Deepstream
GStreamer
Holoscan
ROS/ROS2
OpenCV
PCL

Job description

About the Role

You will work on building and optimizing 3D perception systems that enable robots to understand and interact with complex real-world environments. The goal is to develop robust perception pipelines that work reliably across both simulation and real-world construction sites, ensuring accurate scene understanding, localization, and decision-making.

Key Responsibilities
3D Perception Development & Scene Understanding
  • Design, implement, and deploy realtime 3D perception pipelines leveraging LiDAR, IMU, Stereo, and RGB cameras.
  • Develop algorithms for spatial and temporal data interpretation to enable high-fidelity semantic scene understanding.
  • Optimize ego-motion estimation and localization modules to ensure seamless integration with downstream planning and control tasks.
Deep Learning
  • Train and integrate deep learning models required for semantic world understanding and surface finish classification for quality control
  • Collect and curate high-quality datasets (real and synthetic) and automate training pipelines and experiment tracking.
  • Benchmark and optimize perception models for edge devices to ensure real-time performance in resource-constrained environments
Sensor Fusion & Localization
  • Design and implement sensor fusion strategies combining visual, inertial, and spatial data
  • Architect and implement sophisticated sensor fusion strategies that integrate classical methods with deep learning approaches to convert noisy, asynchronous data from heterogeneous sensors into a unified environment representation.
Calibration
  • Develop and automate robust extrinsic and intrinsic calibration procedures (Camera, LiDAR, IMU) using target-based and/or targetless methods.
  • Design and implement algorithms for online calibration drift detection and self-healing to maintain system integrity during long-term deployments.
  • Establish rigorous quantitative metrics to objectively evaluate and certify calibration quality.
Collaboration
  • Partner with Navigation, Manipulation, and Cloud teams to ensure perception outputs are optimized for downstream path planning, grasping, and remote fleet monitoring.
  • Define, track system-level and own system level KPIs and perception metrics to identify regressions across software iterations.
Requirements
  • 5 YoE
  • Strong fundamentals in computer vision and 3D perception
  • Proficiency in C (Python is a plus)
  • Familiarity with PyTorch, TensorRTBasic understanding of Localisation and SLAM
  • Ability to work with real-world data and debug complex systems
Nice to Have
  • Experience with Nvidia Deepstream, GStreamer, Holoscan
  • Experience with ROS/ROS2
  • Hands-on experience with LiDAR, RGB-D cameras, or IMUs
  • Familiarity with OpenCV, PCL, or similar libraries
  • Experience working on robotics or vision-based projects
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