Simulation Developer Intern – Synthetic Data & Object Detection at OKSI

Torrance, California, United States -

Full Time

Start Date

Immediate

Expiry Date

26 May, 26

Salary

40.0

Posted On

25 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Unreal Engine, Blender, Python, C++, 3D Modeling, Simulation, Data Generation, Object Detection, Segmentation, Machine Learning, Computer Vision, Dataset Validation, 3D Graphics, Real-time Rendering, Automation, Sensor Simulation

Industry

Defense and Space Manufacturing

Description

Description We are seeking a Simulation Developer Intern to support the design and development of high-fidelity synthetic environments and automated data generation pipelines used for object detection and machine learning model training. This role works alongside senior engineers to build real-time 3D simulation scenes, generate labeled datasets, and integrate synthetic outputs into ML workflows. The internship provides hands-on experience in simulation engineering, dataset development, and computer vision systems supporting defense and commercial applications. What You Will Do Build and modify 3D simulation environments using Unreal Engine Create and optimize 3D models, materials, and textures in Blender Configure lighting, weather, and camera perspectives for realistic scenes Generate labeled synthetic image and video datasets Assist with bounding box and segmentation ground truth extraction Support dataset organization, validation, and quality check. Help automate data export and labeling workflows Collaborate with machine learning engineers to support model training Participate in testing, troubleshooting, and performance optimization Requirements Required Qualifications Currently pursuing or recently completed a degree in Computer Science, Computer Engineering, Robotics, Game Development, or a related technical field Experience with Unreal Engine (UE4/UE5) or similar real-time rendering platform Experience with Blender or comparable 3D modeling software Familiarity with Python, C++, or scripting for automation Foundational understanding of 3D graphics, simulation environments, or game engine concepts Basic understanding of computer vision concepts such as object detection or segmentation Strong analytical skills and attention to detail Ability to manage multiple technical tasks and follow established development workflows Clear written and verbal communication skills Preferred but Not Required Experience generating synthetic datasets for machine learning Experience implementing domain randomization techniques Familiarity with PyTorch or other ML frameworks Shader programming experience Experience with sensor simulation (EO, IR, thermal) Background in autonomy, robotics, or defense applications Work Environment and Schedule Onsite, full-time internship position Standard business hours Pay and Benefits Hourly pay range: $20.00 to $40.00 per hour (dependent on experience and qualifications) Additional Requirements To comply with U.S. Government export control regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U.S. person as defined by law. A U.S. person includes a U.S. citizen, lawful permanent resident, or protected individual as defined by 8 U.S.C. § 1324b(a)(3), or an individual otherwise eligible to obtain the required authorization from the U.S. Department of State. We are an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other status protected by law. We provide reasonable accommodations for qualified individuals with disabilities in the application and hiring process. The person hired will have access to information and items subject to U.S. export controls, and therefore, must either be a “U.S. person” as defined by 22 C.F.R. This employer participates in E-Verify.

Responsibilities

The intern will support the design and development of high-fidelity synthetic environments and automated data generation pipelines for object detection and machine learning training. This involves building 3D simulation scenes, generating labeled datasets, and integrating synthetic outputs into ML workflows.