Simulation Engineer

SFE; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

SFE is seeking a Principal Physics and Simulation Engineer to drive advanced simulation and digital twin initiatives in a remote, fulltime role.

You will define physics models, calibrate against measurements, and optimize performance for robotics and AI validation.

Remote work in the United States with cross‑functional collaboration with robotics, sensor, rendering and QA teams.

Qualifications

• Advanced simulation, robotics, or applied physics experience.
• Strong fundamentals in dynamics and kinematics.
• Ability to balance fidelity, stability, and performance.

Responsibilities

• Lead physically credible simulation design for machines and robots.
• Define physics models, assumptions, numerical methods, calibration approach, and acceptance criteria.
• Model rigid-body dynamics, contacts, joints, kinematics, actuation, friction and environment effects.
• Calibrate simulation against measurements and quantify model error, sensitivity and uncertainty.
• Guide implementation, performance optimization, scenario definition, and validation.
• Collaborate with digital twin, robotics, sensor, rendering, and QA engineers.

Skills

Advanced simulation

Dynamics fundamentals

Calibration & validation

Robotics experience

Tools

PhysX

Isaac Sim

Modelica

MATLAB/Simulink

Job description

Position: Principal Physics and Simulation Engineer

Location: Remote

Duration: Fulltime

Job Description

Must Have Technical/Functional Skills

• Advanced simulation, computational engineering, robotics, mechatronics, or applied physics experience.
• Strong fundamentals in dynamics, kinematics, numerical simulation, calibration, and validation.
• Ability to balance fidelity, stability, performance, and intended use.

Good to Have

• PhysX, Isaac Sim, Modelica, MATLAB/Simulink, multibody dynamics, FEA/CFD interfaces, or real-time simulation.

Roles & Responsibilities

• Lead physically credible simulation design for machines, robots, sensors, materials, environments, and industrial processes used in engineering and AI validation.
• Define physics models, assumptions, numerical methods, calibration approach, and acceptance criteria.
• Model rigid-body dynamics, contacts, joints, kinematics, actuation, friction, and relevant environmental effects.
• Calibrate simulation against measurements and quantify model error, sensitivity, and uncertainty.
• Guide implementation, performance optimization, scenario definition, and validation.

Collaboration & Leadership

• Guide implementation and work with digital twin, robotics, sensor, rendering, and QA engineers.