Junior/Senior and Graduate 1 Intern

Overview

The hourly rate for this position is $17.75 for Undergraduate II and $22.84 for Graduate I and is non-negotiable.

This Statement of Work covers the need for student services to provide Test and Evaluation (T&E) engineering support for multi-modal simulation environments. Employs a software engineering iterative approach to develop automation frameworks and test cases using current engineering tools, such as Python-based testing frameworks, containerization technologies, and cloud-based infrastructure design to validate and verify technical solutions. Responsible for assisting in the validation and maintenance of a multi-container testbed, aids in the evaluation of external performer agents across various military scenarios and creates automated test suites and data analysis processes to measure agent performance against DARPA-defined metrics.

ERIS aims to research and develop a range of technical solutions through the use of multi-modal simulation, container-based orchestration, automated Test and Evaluation (T&E) frameworks, and visualization capabilities that enable users to observe and assess complex multi-agent interactions. This development is critical to ERIS’s mission because it provides a scalable testbed for existing and future DARPA programs and supports agent understanding of complex military scenarios across multiple operational domains.

At the undergraduate level, student contractors will apply fundamental software engineering and computer science techniques to help ensure that simulation models, external agents, supporting services, and test infrastructure operate predictably, reliably, and consistently. Undergraduate efforts may include software development, test automation, containerization, data handling, documentation, integration support, and implementation of simulation-test capabilities under government and senior technical staff guidance.

At the graduate level, student contractors will focus on the design, development, and improvement of visualization capabilities for game and simulation environments used to test and evaluate multiple learning agents. This work will support the visualization of terrain, scenario context, agent states, movement, interactions, decisions, events, and performance measures across concurrent simulation runs. Graduate-level efforts may include developing interactive two-dimensional and three-dimensional displays; simulation-control and scenario-configuration interfaces; dashboards; agent-behavior visualizations; event timelines; replay tools; and after-action analysis products.

The graduate student will help translate simulation data and learning-agent telemetry into clear, interpretable visual representations that enable government developers, test personnel, and researchers to assess agent behavior, compare alternative courses of action, identify anomalous or emergent behavior, and evaluate system performance. The student may also support integration of visualization components with simulation engines, agent frameworks, automated T&E pipelines, containerized services, and data-collection mechanisms.

By applying advanced software engineering, visualization, human-computer interaction, simulation, and machine-learning-adjacent techniques, the graduate student will contribute to a usable and scalable environment for observing, testing, and evaluating learning agents in representative multi-domain scenarios.

Responsibilities

The student contractor shall provide technical support in the following areas, as specified under individual task orders, to the work sponsor:

Software Engineering, Programming:

• Designing, developing, testing, and documenting automated testbed architectures and frameworks for a multi-modal simulation platform.
• Assist with ERIS’s AWS cloud infrastructure (EC2, S3, deployment, and containerization).
• Assist with developing and integrating Continuous Integration/Continuous Deployment (CI/CD) pipelines to automate the testing and deployment of test and evaluation tools.
• Reviewing technical documentation and coordinating with work sponsor(s) to resolve requirements ambiguities and ensure process adherence.
• Installing, integrating, and troubleshooting software applications and configurations within a cloud-based (AWS) environment.

Qualifications

Undergrad II: The student must be at the Junior or Senior level and have experience in 50% of the task requirements and be able to accomplish 50% of the work independently. Is not required to be an SDSU Student.

Computer Science major preferred; relevant majors such as Data Science and Software Engineering be suitable given relevant coursework and/or work experience.

Required Coursework and/or relevant work and/or laboratory experience:

• MATH 245 Discrete Mathematics (or equivalent)
• MATH 254 Introduction to Linear Algebra (or equivalent)

Desired Coursework and/or relevant work and/or laboratory experience:

• CS 210 Data Structures (or equivalent)
• CS 250 Introduction to Software Systems (or equivalent)
• CS 532 Software Engineering (or equivalent)

Additional Qualifications Desired:

• Python, or web-development or software programming experience.
• Experience with AGILE methodology.
• Experience with GIT and version control.
• Experience in machine learning.
• Ability to read and implement technical documents or test standards.
• Comfortable with working independently and in group settings.
• Flexible with learning new programming languages based on project’s needs.
• Knowledge in Docker/containers.
• Experience in deploying software.
• Experience with cloud computing/architecture (AWS, Azure).
• Ability to read and implement technical documents or test standards.
• Independent/self-starter who can operate under minimal oversight.
• Collaborative/team-player who can work well with groups.
• Experience writing unit tests (ex. Pytest, Jest, etc)

Graduate I: Graduate Student 1: Must have a Bachelor's degree in the required discipline and be enrolled in a Master's degree program. Must be able to accomplish a minimum of 50% of the task without supervision.

Pursuing a master’s or doctoral degree in Computer Science, Software Engineering, Data Science, Game Development, Computer Graphics, Human-Computer Interaction, Visualization, Electrical/Computer Engineering, or a closely related technical discipline. The student will support development of visual game and simulation environments used to observe, assess, and test multiple learning agents, including government-developed red agents and AI course-of-action generation agents.

Required Coursework and/or Relevant Work and/or Laboratory Experience:

• Data Structures and Algorithms, or equivalent software-development experience.
• Software Engineering, Software Systems, or equivalent experience developing maintainable, tested software.
• Linear Algebra, Computer Graphics, Visualization, or equivalent coursework supporting spatial representations, rendering, and visual analytics.
• Human-Computer Interaction, User Interface/User Experience Design, Game Development, Simulation, or equivalent experience.
• Demonstrated experience developing interactive visual applications, game environments, simulation interfaces, dashboards, or data-visualization tools.

Additional Qualifications Desired

• Proficiency in Python, JavaScript/TypeScript, C#, C++, or other languages applicable to simulation, visualization, game-engine, or web-development work.
• Experience with game engines or visualization frameworks, such as Unity, Unreal Engine, Godot, WebGL, Three.js, React, D3.js, or comparable tools.
• Experience creating 2D or 3D visual environments that display terrain, entities, movement, interactions, events, and agent decisions.
• Experience developing visualization tools for autonomous systems, multi-agent systems, simulations, games, robotics, or decision-support applications.
• Experience representing agent state, actions, objectives, routes, behavior changes, and interactions in a clear and interpretable visual format.
• Experience developing user interfaces that allow test personnel to configure scenarios, initialize agents, control simulation execution, inspect outcomes, and replay test runs.
• Familiarity with visual analytics methods for comparing multiple agent behaviors, including timelines, heat maps, event logs, performance charts, decision traces, and after-action visualizations.
• Experience integrating visualization components with simulation engines, agent frameworks, APIs, databases, telemetry streams, or distributed software systems.
• Familiarity with machine learning, reinforcement learning, multi-agent systems, or autonomous-agent concepts sufficient to visualize agent training, behavior, and evaluation results.
• Experience designing displays that support assessment of agent performance, robustness, adaptability, repeatability, and emergent behavior.
• Experience with scenario playback, event logging, data capture, serialization, and reproducible experiment workflows.
• Experience optimizing visualization or game-environment performance for multiple simultaneous agents, large scenario areas, high event volumes, or near-real-time data updates.
• Experience with Docker, containers, environment management, and reproducible development or deployment workflows.
• Experience deploying software applications or services in local, cloud, or containerized environments; familiarity with AWS, Azure, or comparable platforms is desired.
• Experience with Git and collaborative version-control workflows, including branching, pull requests, code review, and issue tracking.
• Experience using Agile, Scrum, Kanban, or similar iterative software-development methodologies.
• Experience writing automated tests, including unit, integration, UI, regression, and scenario-based tests using tools such as Pytest, Jest, Playwright, or comparable frameworks.
• Ability to read, interpret, and implement technical documentation, interface-control documents, test plans, test standards, and visualization requirements.
• Ability to document software architecture, user-interface designs, data schemas, visualization assumptions, test results, and known limitations clearly.
• Independent/self-starter able to identify usability, performance, data-integration, and visualization risks and propose practical solutions under minimal oversight.
• Collaborative/team-player able to work effectively with government developers, learning-agent developers, simulation engineers, testers, analysts, and other student contractors.
• Flexible and able to learn new visualization frameworks, game engines, programming languages, simulation interfaces, and domain concepts as project requirements evolve.

ADDITIONAL APPLICANT INFORMATION:

• This position will require the employee to obtain and maintain a DoD Secret security clearance
• Due to the regulations established by the Department of Defense, only US Citizens may qualify
• This is a student position and is limited to working 20 hours per week
• This position will remain open until filled
• Candidate must reside in California and live within a commutable distance from SDSU at time of hire.
• Job offer is contingent upon satisfactory clearance based on background check results (including a criminal record check).
• San Diego State University Research Foundation is an equal opportunity employer. Consistent with California law and federal civil rights laws, SDSU Research Foundation provides equal opportunity in employment without unlawful discrimination or preferential treatment based on race, sex, color, ethnicity, or national origin or any other categories protected by federal or state law.  
• Employment decisions are based on an individual’s qualifications as they relate to the job under consideration. Our commitment to equal opportunity means ensuring that every employee has equal access to resources and support. 
• SDSU Research Foundation complies with Titles VI and VII of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, the Americans with Disabilities Act (ADA), Section 504 of the Rehabilitation Act, the California Equity in Higher Education Act, California’s Proposition 209 (Art. I, Section 31 of the California Constitution), and other applicable state and federal anti-discrimination laws including grant or contract terms and conditions related to funded program activities. Further the SDSU Research Foundation maintains a Nondiscrimination Policy that prohibits discriminatory preferential treatment, segregation based on race or any other protected status, and all forms of unlawful discrimination, harassment, and retaliation in all programs, policies, and practices.  
• SDSU Research Foundation makes all employment decisions including, but not limited to, applicant screening, hiring, promotion, demotion, compensation, benefits, disciplinary actions, and terminations on the basis of merit.