Dein persönlicher KI-Karriere-Agent
Robotics Engineer - Modeling & Sim-to-Real Transfer(m/w/x)
Modeling and system identification for humanoid robots, characterizing physical hardware. Multi-body dynamics and C++/Python coding skills required. Energetic team, competitive compensation.
Anforderungen
- MSc or PhD in Robotics, Mechanical Engineering, Electrical Engineering, or equivalent experience
- Strong background in multi-body dynamics, numerical methods, and robot physics
- Proven experience in system modeling and identification for physical systems
- Strong coding skills in C++ and Python
- Hands-on experience with modern simulators (e.g., Isaac Lab/Gym, MuJoCo, Drake)
- Hands-on experience with real robotic hardware, experiments, and system-level debugging
- Deep knowledge of actuator dynamics (BLDC motors, gearboxes, friction models)
- Deep knowledge of sensor modeling (IMUs, LiDARs, cameras)
- Familiarity with Reinforcement Learning
- Experience with robot description formats (URDF, SDF, USD)
Aufgaben
- Model in-house and customer robots accurately
- Perform system identification for robots
- Characterize physical hardware sensors
- Characterize physical hardware drivetrains
- Characterize physical hardware contact dynamics
- Replicate robot behaviors in simulation
- Evaluate the sim-to-real gap
- Develop mathematical models for physical subsystems
- Model drivetrain behavior
- Model sensor behavior
- Model network behavior (latency, jitter)
- Design experiments to collect robot data
- Execute experiments to collect robot data
- Identify physical parameters using robot data
- Identify friction coefficients
- Identify inertial parameters
- Identify noise parameters
- Identify latency parameters
- Implement models into simulation infrastructure
- Benchmark simulation performance against real-world logs
- Quantify the Sim-to-Real gap
- Minimize the Sim-to-Real gap
- Collaborate with control teams
- Collaborate with perception teams
- Collaborate with hardware teams
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- C++
- Python
- Isaac Lab/Gym
- MuJoCo
- Drake
- URDF
- SDF
- USD
Benefits
Attraktive Vergütung
- Competitive compensation
Lockere Unternehmenskultur
- Energetic, collaborative team
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Robotics Engineer - Modeling & Sim-to-Real Transfer(m/w/x)
Modeling and system identification for humanoid robots, characterizing physical hardware. Multi-body dynamics and C++/Python coding skills required. Energetic team, competitive compensation.
Anforderungen
- MSc or PhD in Robotics, Mechanical Engineering, Electrical Engineering, or equivalent experience
- Strong background in multi-body dynamics, numerical methods, and robot physics
- Proven experience in system modeling and identification for physical systems
- Strong coding skills in C++ and Python
- Hands-on experience with modern simulators (e.g., Isaac Lab/Gym, MuJoCo, Drake)
- Hands-on experience with real robotic hardware, experiments, and system-level debugging
- Deep knowledge of actuator dynamics (BLDC motors, gearboxes, friction models)
- Deep knowledge of sensor modeling (IMUs, LiDARs, cameras)
- Familiarity with Reinforcement Learning
- Experience with robot description formats (URDF, SDF, USD)
Aufgaben
- Model in-house and customer robots accurately
- Perform system identification for robots
- Characterize physical hardware sensors
- Characterize physical hardware drivetrains
- Characterize physical hardware contact dynamics
- Replicate robot behaviors in simulation
- Evaluate the sim-to-real gap
- Develop mathematical models for physical subsystems
- Model drivetrain behavior
- Model sensor behavior
- Model network behavior (latency, jitter)
- Design experiments to collect robot data
- Execute experiments to collect robot data
- Identify physical parameters using robot data
- Identify friction coefficients
- Identify inertial parameters
- Identify noise parameters
- Identify latency parameters
- Implement models into simulation infrastructure
- Benchmark simulation performance against real-world logs
- Quantify the Sim-to-Real gap
- Minimize the Sim-to-Real gap
- Collaborate with control teams
- Collaborate with perception teams
- Collaborate with hardware teams
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- C++
- Python
- Isaac Lab/Gym
- MuJoCo
- Drake
- URDF
- SDF
- USD
Benefits
Attraktive Vergütung
- Competitive compensation
Lockere Unternehmenskultur
- Energetic, collaborative team
Über das Unternehmen
Flexion Robotics
Branche
Engineering
Beschreibung
Flexion builds the intelligence layer for next-gen humanoid robots, accelerating their real-world deployment.
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