Robotics Perception & State Estimation Engineer - Humanoid (human)

NEURA Robotics; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

NEURA Robotics in Zürich, Switzerland seeks a Robotics Perception & State Estimation Engineer to build production-grade perception systems for humanoid robots, spanning sensor integration to world modeling and deployment on real platforms.

You will own components of the perception stack, develop real-time pipelines with ROS2 and DDS, and collaborate with controls and planning teams to ensure reliable robot-wide behavior in dynamic environments.

Qualifikationen

• 3+ years of professional experience building robotic perception systems.
• Own components of a perception stack from sensor integration to deployment.
• Strong C++ software engineering with production-quality code.
• Experience with ROS2 and distributed robotic systems.
• Familiarity with real-time sensor pipelines and TF timing management.
• Hands-on integration of cameras, LiDAR, IMUs, encoders.
• Experience with localization, mapping, and state estimation.

Aufgaben

• Own design, development, and deployment of production-grade perception systems.
• Architect robust perception software stacks for real-time operation.
• Develop state estimation, localization, SLAM, and sensor fusion.
• Integrate diverse sensing modalities into a coherent world model.
• Design and maintain ROS2 middleware and data pipelines.
• Validate perception capabilities on simulation and real robots.

Kenntnisse

ROS2

DDS

C++17/20

Sensor fusion

SLAM

Localization

World modeling

Ausbildung

Bachelor's degree in Computer Science or related field

Master's degree in Robotics or related field

Tools

PCL

OpenCV

Gazebo

Jetson platforms

Jobbeschreibung

Your mission & challenges

As a Robotics Perception & State Estimation Engineer, you will develop the core perception capabilities that allow our humanoid robots to understand, localize within, and interact with the physical world.

This role is not focused solely on developing perception algorithms or training machine learning models. We are looking for engineers who can build and own complete perception systems, from sensor integration and calibration through localization, sensor fusion, world modeling, and deployment on real robotic platforms.

You will work at the intersection of perception, state estimation, robotics software infrastructure, and system integration. Your contributions will directly impact navigation, manipulation, safety, and human-robot interaction.

• Own the design, development, and deployment of production-grade perception systems for humanoid robots, transforming raw sensor data into reliable world understanding for navigation, manipulation, and human-robot interaction.

• Architect robust perception software stacks that operate under real-time constraints, from sensor acquisition and calibration to localization, scene understanding, and world modeling.

• Develop and improve state estimation, localization, mapping, SLAM, and sensor fusion systems that enable robots to operate reliably in dynamic real-world environments.

• Integrate, calibrate, and synchronize diverse sensing modalities including cameras, stereo and depth sensors, LiDAR, IMUs, force/torque sensors, and joint encoders into a coherent representation of the robot and its surroundings.

• Design and maintain high-performance ROS2 middleware like and DDS and Zenoh based data pipeline, ensuring reliable communication, timing, synchronization, and coordinate-frame management across the perception stack.

• Build, optimize, and maintain core perception capabilities including:

  • SLAM and localization

  • Sensor fusion and state estimation

  • 3D reconstruction and world modeling

  • Object detection, tracking, and scene understanding

  • Semantic and geometric environment representation

• Evaluate, integrate, and deploy learning-based perception solutions where they provide clear advantages, while balancing robustness, maintainability, and real-time performance.

• Diagnose and resolve complex system-level issues involving calibration, synchronization, localization drift, sensor reliability, communication bottlenecks, and perception performance.

• Develop tools and frameworks for visualization, debugging, validation, and continuous performance monitoring of perception systems.

• Validate and benchmark perception capabilities in simulation and on physical humanoid robots, ensuring seamless transfer from development environments to real-world deployment.

• Collaborate closely with controls, manipulation, planning, and platform teams to define interfaces, requirements, and system architectures that enable reliable robot-wide behavior.

• Drive long-term technical direction for perception architecture, software quality, testing, maintainability, and system scalability.

What we can look forward to

• Bachelor's or Master's degree in Computer Science, Software Engineering, Robotics, or a related technical field.

• 3+ years of professional experience building and deploying complex robotic perception systems, not just individual perception algorithms or ML models.

• Proven ownership of key components of a perception stack, such as sensor integration, calibration, localization, mapping, sensor fusion, state estimation, or real-world deployment.

• Hands-on experience with one or more of the following:

  • Visual, LiDAR, or Visual-Inertial SLAM

  • Localization and mapping

  • Sensor fusion and state estimation

  • Factor graph optimization

  • EKF/UKF-based systems

• Strong understanding of robotics software architectures, including:

  • ROS2 and DDS

  • Distributed robotic systems

  • High-throughput sensor pipelines

  • Synchronization, timing, and coordinate frame management (TF)

• Practical experience integrating and debugging perception sensors, including cameras, LiDARs, IMUs, force/torque sensors, and encoders.

• Strong software engineering skills with modern C++ (C++17/20), multi-threaded systems, performance optimization, and production-quality code development.

Nice to have

• Perception for humanoids, manipulation, or autonomous robots

• GPU acceleration

• Embedded robotics systems

• NVIDIA Jetson platforms

• Deep learning for perception

• PyTorch or TensorFlow

• PCL, OpenCV

• IsaacSim, Mojuko or Gazebo

• MLOps experience