Simulation Realism Engineer Internship - Summer 2026

Location: Sausalito, California, United States

Department: Engineering

Workplace: on_site

Employment Type: temporary

Description

Company Description

iMETALX, Inc. is pioneering innovations in space accessibility and sustainability. Our mission is to deliver cutting-edge solutions in space domain awareness (SDA) and in-space servicing, assembly, and manufacturing (ISAM) to both government and commercial sectors. Our focus encompasses spacecraft autonomy, leveraging advanced technologies in perception, controls, and testing in real-world systems.

As we expand our team, we are seeking passionate and innovative minds to join us in shaping the future of space technology. iMETALX offers exciting internships that provide hands-on experience in a fast-paced environment where ideas can flourish. The Simulation Realism Engineer Internship is an opportunity for students to gain valuable insights and practical skills in high-fidelity simulation development for space applications.

Role Overview:

As a Simulation Realism Engineer Intern, you will assist in the creation and enhancement of synthetic simulation environments that closely mimic real-world scenarios relevant to our ISAM and SDA missions. This internship will provide you with the unique chance to work alongside experienced engineers on projects that bridge the gap between simulation and reality, ensuring that our autonomy systems perform efficiently in the field.

Your contributions will involve working with various simulation tools and methodologies, developing realistic scenarios, and supporting our engineers in validating these simulations through rigorous testing. You will gain firsthand experience in applying theories learned in the classroom to real-world challenges at the frontier of space technology.

What You’ll Learn

Your internship will focus on:

• Understanding and implementing high-fidelity simulation techniques
• Participating in data generation and the development of realism metrics
• Collaborating with engineers to improve simulation systems
• Learning about physics-based modeling and its application in a space environment

Key Responsibilities:

Assisting with simulation development

• Support the design and implementation of synthetic scene generation pipelines
• Contribute to the creation of datasets for training and testing autonomy systems

Analyzing and improving simulation realism

• Participate in identifying realism gaps and suggest metrics for improvement
• Help assist in building regression tests to maintain simulation fidelity

Collaboration

• Work closely with other interns and engineers to enhance tool usability and effectiveness

Who You Are

• A motivated undergraduate or graduate student pursuing a degree in Aerospace Engineering, Robotics, Computer Science, Applied Mathematics, or a related field.
• Familiarity with programming, preferably in Python or C++.
• Basic understanding of principles related to physics-based modeling and simulation.
• You possess strong analytical skills with a desire to learn about simulation technologies.
• A collaborative team player who communicates effectively and seeks to absorb knowledge from experienced professionals.
• Committed to personal growth and the advancement of innovative simulation practices.

Requirements

Required Qualifications

• Currently enrolled in an undergraduate or graduate program (Aerospace Engineering, Robotics, Computer Science, Applied Mathematics, or related areas).
• Basic programming skills in Python and/or C++.
• Strong analytical and problem-solving capabilities.
• Interest in simulation technologies and robotics/autonomy systems.
• Ability to work effectively in a collaborative team environment.
• Ability and willingness to work on-site in Sausalito, CA during the summer of 2026.

Preferred Qualifications

• Previous internship experience or coursework in simulation, modeling, or autonomous systems.
• Familiarity with simulation/graphics platforms (e.g., Unreal Engine, Unity, Gazebo).
• An understanding of visual and sensor modeling.