Robotics Software Engineer – SLAM

United Robots; Warszawa; On-site; PLN 150,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation

Hands-on robotics testing

Collaboration with engineering teams

Job summary

United Robots is seeking a Robotics Software Engineer specializing in SLAM, localisation, and mapping. You will develop algorithms to determine robot position reliably in large, dynamic industrial environments and integrate data from LiDARs, cameras, IMUs, and other sensors.

The role involves implementing loop closure, relocalisation, and drift reduction, validating maps, and testing in simulation and on real robots.

Qualifications

• Minimum of 2 years of relevant professional experience.
• Experience developing SLAM, localisation, odometry, or state-estimation algorithms.
• Practical knowledge of ROS or ROS 2.
• Good knowledge of C++ and/or Python.
• Knowledge of LiDAR-, camera-, IMU-, or multi-sensor-fusion methods.
• Knowledge of 2D and 3D geometry, coordinate transformations, and matrix calculus.
• Knowledge of Kalman filters, particle filters, graph optimisation, or similar estimation methods.
• Experience processing point clouds or images.
• Ability to assess map and trajectory quality.
• Experience working with real sensor data.
• Very good knowledge of Linux and Git.
• English proficiency sufficient to work confidently with technical documentation and research papers.

Responsibilities

• Developing SLAM and mobile robot localisation algorithms.
• Designing and implementing 2D LiDAR SLAM, 3D LiDAR SLAM, Visual SLAM, or Visual-Inertial SLAM solutions.
• Developing and optimising localisation algorithms for previously created maps.
• Integrating data from LiDARs, cameras, IMUs, encoders, and other sensors.
• Developing sensor-fusion and robot-state-estimation algorithms.
• Implementing loop closure, relocalisation, and lost-position detection mechanisms.
• Developing tools for creating, updating, merging, and validating maps.
• Detecting environmental changes and reducing the impact of dynamic objects on mapping.
• Improving system performance in repetitive environments, long corridors, and areas with few distinctive features.
• Performing intrinsic and extrinsic sensor calibration and verifying coordinate-frame transformations.
• Developing SLAM and localisation components in ROS and ROS 2.
• Optimising algorithms for real-time operation on onboard computers.
• Preparing and analysing datasets and robot-operation logs.
• Defining localisation and mapping quality metrics.
• Creating automated benchmark and regression tests.
• Testing solutions in simulation and on physical robots.
• Diagnosing issues encountered during deployments and customer operation.
• Collaborating with navigation, control, sensor-integration, and embedded teams.
• Preparing technical documentation for developed solutions.

Skills

SLAM

Localization

State estimation

Robot perception

English technical docs

Tools

ROS/ROS 2

C++

Python

Point clouds / sensors

Job description

United Robots is a technology company developing autonomous mobile robots for industrial facilities, warehouses, and logistics centres. We create complete solutions encompassing electronics, control systems, autonomous navigation, sensor integration, robot software, and a cloud platform for managing fleets of devices.

We are looking for a Robotics Software Engineer specialising in SLAM, localisation, and mapping. In this role, you will develop algorithms that enable robots to determine their position reliably and operate in large, dynamic, and frequently repetitive industrial environments.

Responsibilities

• Developing SLAM and mobile robot localisation algorithms;
• Designing and implementing 2D LiDAR SLAM, 3D LiDAR SLAM, Visual SLAM, or Visual-Inertial SLAM solutions;
• Developing and optimising localisation algorithms for previously created maps;
• Integrating data from LiDARs, cameras, IMUs, encoders, and other sensors;
• Developing sensor-fusion and robot-state-estimation algorithms;
• Implementing loop closure, relocalisation, and lost-position detection mechanisms;
• Developing tools for creating, updating, merging, and validating maps;
• Detecting environmental changes and reducing the impact of dynamic objects on mapping;
• Improving system performance in repetitive environments, long corridors, and areas with few distinctive features;
• Performing intrinsic and extrinsic sensor calibration and verifying coordinate-frame transformations;
• Developing SLAM and localisation components in ROS and ROS 2;
• Optimising algorithms for real-time operation on onboard computers;
• Preparing and analysing datasets and robot-operation logs;
• Defining localisation and mapping quality metrics;
• Creating automated benchmark and regression tests;
• Testing solutions in simulation and on physical robots;
• Diagnosing issues encountered during deployments and customer operation;
• Collaborating with navigation, control, sensor-integration, and embedded teams;
• Preparing technical documentation for developed solutions.

Key objectives of the role

• Increasing the accuracy and stability of robot localisation;
• Ensuring reliable operation in large and changing industrial facilities;
• Reducing lost-position events and the need for manual relocalisation;
• Developing a shared mapping and localisation system for different robot models;
• Reducing the time required to prepare new customer locations;
• Increasing system resilience to dynamic objects, environmental changes, and sensor disturbances;
• Preparing SLAM solutions to scale across a growing robot fleet.

Requirements

• A minimum of 2 years of relevant professional experience;
• Experience developing SLAM, localisation, odometry, or state-estimation algorithms;
• Practical knowledge of ROS or ROS 2;
• Good knowledge of C++ and/or Python;
• Knowledge of LiDAR-, camera-, IMU-, or multi-sensor-fusion methods;
• Knowledge of 2D and 3D geometry, coordinate transformations, and matrix calculus;
• Knowledge of Kalman filters, particle filters, graph optimisation, or similar estimation methods;
• Experience processing point clouds or images;
• Ability to assess map and trajectory quality;
• Experience working with real sensor data;
• Very good knowledge of Linux and Git;
• Ability to diagnose issues using logs, rosbags, and telemetry;
• English proficiency sufficient to work confidently with technical documentation and research papers.

Nice to have

• Experience with Cartographer, SLAM Toolbox, RTAB-Map, LIO-SAM, FAST-LIO, ORB-SLAM, VINS-Fusion, or similar solutions;
• Knowledge of PCL, OpenCV, Eigen, Ceres Solver, or GTSAM;
• Experience with ICP, NDT, scan matching, and feature matching;
• Knowledge of factor graphs and pose-graph optimisation;
• Experience with AMRs or AGVs;
• Experience in industrial and warehouse environments;
• Knowledge of Gazebo, Isaac Sim, or other simulation environments;
• Experience with NVIDIA Jetson or industrial edge computers;
• Knowledge of Docker, CI/CD, and test automation;
• Experience with multi-robot systems or shared maps;
• Publications, open-source contributions, or personal SLAM implementations.

What we offer

• A genuine influence on the localisation and mapping system of autonomous robots;
• Work with real data and robots operating at customer sites;
• The opportunity to develop 2D, 3D, and vision-based solutions;
• Access to robots, LiDARs, cameras, IMUs, and a dedicated testing environment;
• The opportunity to test algorithms in large industrial facilities;
• A high degree of independence and direct cooperation with the technical team;
• Participation in developing new products and future robot generations;
• Compensation aligned with your experience and level of responsibility.