Perception Specialist

As a Perception Specialist, you will design and implement cutting-edge perception algorithms that enhance robotic vision, SLAM, sensor fusion, and environmental modeling. Your work will enable robots to perceive, localize, and respond intelligently in complex environments. You will collaborate with AI/ML teams, robotics engineers, and hardware specialists to integrate perception systems seamlessly into autonomous robotic platforms.

Key Responsibilities

1. Development of Perception Algorithms

• Design Advanced Perception Systems: Develop real-time perception algorithms for object detection, obstacle avoidance, and environment modeling.
• Enhance Localization & Mapping: Implement SLAM algorithms using data from LiDAR, cameras, and IMUs to provide precise real-time localization for robotic systems.
• Implement Multi-Sensor Fusion: Combine sensor data from LiDAR, cameras, radar, and depth sensors to create an accurate and comprehensive environmental model.

2. Environmental Understanding & Modeling

• Generate 3D Maps & Models: Utilize point cloud data from LiDAR and stereo cameras to construct detailed 3D maps of environments.
• Adapt to Dynamic Environments: Develop algorithms for real-time moving object detection, tracking, and adaptive scene interpretation.
• Enable Context-Aware Decision-Making: Implement semantic segmentation and scene parsing to enhance robotic decision-making in real-world conditions.

3. Integration with Robotic Platforms

• Seamless Perception System Integration: Work with robotics and software teams to integrate perception algorithms into autonomous robotic systems.
• Sensor Calibration & Alignment: Configure and calibrate LiDAR, cameras, and IMUs to ensure accurate data alignment and synchronization.
• Optimize for Real-Time Robotics Applications: Deploy low-latency perception models on embedded AI platforms for real-time robotic navigation and manipulation.

4. Research & Innovation

• Explore Emerging Perception Technologies: Stay up-to-date with advancements in graph neural networks, transformer-based vision models, neuromorphic vision, and AI-driven sensor fusion.
• Prototype Advanced Perception Solutions: Develop proof-of-concept models to test new approaches in robotic perception and sensing.
• Contribute to Research & Open-Source Initiatives: Engage in cutting-edge R&D projects and contribute to open-source perception frameworks.

5. Testing, Validation & Optimization

• Rigorous Testing in Diverse Conditions: Validate perception algorithms in varied industrial, indoor, and outdoor environments.
• Optimize for Edge AI & Embedded Systems: Adapt perception models for low-power, high-performance deployment on NVIDIA Jetson, ARM Cortex, and FPGA platforms.
• Continuously Improve Performance: Monitor and refine perception systems to ensure consistent and reliable real-world performance.

6. Collaboration & Knowledge Sharing

• Cross-Functional Team Collaboration: Work closely with robotics engineers, AI/ML researchers, and hardware teams to align perception development with robotic system objectives.
• Document & Standardize Perception Workflows: Maintain detailed documentation of perception algorithms, methodologies, and best practices.
• Communicate Insights & Technical Progress: Present findings, metrics, and advancements to stakeholders and contribute to organizational knowledge sharing.

Required Qualifications - Education & Experience

• Bachelors or Masters degree in Robotics, Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in robotic perception, sensor fusion, or SLAM development.
• Proven track record of developing perception algorithms and working with real-world robotic sensing challenges.

Technical Skills

• Computer Vision & Perception Frameworks:
• Proficiency in OpenCV, PCL (Point Cloud Library), PyTorch, or TensorFlow for developing perception algorithms.
• Experience in point cloud processing, object tracking, and scene understanding.
• Programming & Embedded AI Development:
• Strong programming skills in Python and C++.
• Familiarity with CUDA programming for GPU-accelerated perception tasks.
• SLAM & Sensor Fusion:
• Expertise in SLAM algorithms (graph-based SLAM, visual SLAM, LiDAR SLAM).
• Experience integrating data from LiDAR, cameras, IMUs, and radar for real-time perception.
• Robotics & ROS Integration:
• Hands-on experience with Robot Operating System (ROS) for integrating perception systems into robotic platforms.
• Familiarity with Gazebo and RViz for simulation and validation of robotic perception algorithms.

Preferred Qualifications

• Advanced SLAM & Localization Expertise: Deep understanding of multi-modal SLAM approaches, uncertainty estimation, and loop closure techniques.
• Edge AI & Embedded Perception Optimization: Experience optimizing AI-driven perception models for real-time deployment on NVIDIA Jetson, ARM Cortex, or FPGA platforms.
• Optimization & AI Model Acceleration: Familiarity with TensorRT, OpenVINO, ONNX, or custom AI acceleration techniques for embedded perception.
• Domain Knowledge in Industrial Robotics: Understanding of robotic perception applications in industrial automation, autonomous navigation, and smart manufacturing.