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Robotics State Estimation Engineer(m/w/x)
Designing and implementing state estimation pipelines for autonomous systems on heavy industrial machinery. Experience with state estimation algorithms and LiDAR odometry required. Stock options.
Requirements
- Degree in Robotics, Engineering, or related field
- Experience with state estimation algorithms
- Familiarity with LiDAR odometry algorithms
- Experience estimating vehicle motion states
- Experience with sensor calibration
- Proficiency in C++ and/or Python
- Familiarity with ROS or ROS2
- Strong debugging and analytical skills
- Experience in heavy industry robotics
- Knowledge of SLAM and localization
- Familiarity with factor graph libraries
- Understanding of vehicle dynamics
- Experience validating robotics systems
- Comfort working across full stack
Tasks
- Design and implement state estimation pipelines
- Ensure robust estimation of position and velocity
- Fuse multi-sensor data using probabilistic frameworks
- Develop filter-based and optimization-based estimators
- Model sensor noise and failure modes
- Build redundant estimators for failure detection
- Integrate estimation modules with SLAM and control stacks
- Validate performance using simulation and field tests
- Tune and debug estimators in production environments
- Collaborate with cross-functional robotics engineering teams
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Kalman Filters
- EKF
- GTSAM
- Ceres
- g2o
- particle filters
- LiDAR
- C++
- Python
- ROS
- ROS2
Benefits
Competitive Pay
- Attractive compensation package
- Stock options
Career Advancement
- Tailored career path
Informal Culture
- Great team culture
Snacks & Drinks
- Beverages on-site
Modern Office
- Amazing office environment
Team Events
- Regular social events
Additional Allowances
- Relocation assistance to Berlin
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Robotics State Estimation Engineer(m/w/x)
Designing and implementing state estimation pipelines for autonomous systems on heavy industrial machinery. Experience with state estimation algorithms and LiDAR odometry required. Stock options.
Requirements
- Degree in Robotics, Engineering, or related field
- Experience with state estimation algorithms
- Familiarity with LiDAR odometry algorithms
- Experience estimating vehicle motion states
- Experience with sensor calibration
- Proficiency in C++ and/or Python
- Familiarity with ROS or ROS2
- Strong debugging and analytical skills
- Experience in heavy industry robotics
- Knowledge of SLAM and localization
- Familiarity with factor graph libraries
- Understanding of vehicle dynamics
- Experience validating robotics systems
- Comfort working across full stack
Tasks
- Design and implement state estimation pipelines
- Ensure robust estimation of position and velocity
- Fuse multi-sensor data using probabilistic frameworks
- Develop filter-based and optimization-based estimators
- Model sensor noise and failure modes
- Build redundant estimators for failure detection
- Integrate estimation modules with SLAM and control stacks
- Validate performance using simulation and field tests
- Tune and debug estimators in production environments
- Collaborate with cross-functional robotics engineering teams
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Kalman Filters
- EKF
- GTSAM
- Ceres
- g2o
- particle filters
- LiDAR
- C++
- Python
- ROS
- ROS2
Benefits
Competitive Pay
- Attractive compensation package
- Stock options
Career Advancement
- Tailored career path
Informal Culture
- Great team culture
Snacks & Drinks
- Beverages on-site
Modern Office
- Amazing office environment
Team Events
- Regular social events
Additional Allowances
- Relocation assistance to Berlin
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
sensmore
Industry
Manufacturing
Description
The company automates the world's largest machines with unprecedented intelligence, integrating robotics into a platform for productivity and safety.
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