AI/ML Engineer for Human Factors

Join a multidisciplinary research team working on a DARPA-funded projects focused on predicting human performance and enhancement in high-stakes environments such as military operations. In this role, you will contribute to the design and implementation of software tools and analysis pipelines that leverage physiological, behavioral, and communication data to model and predict team effectiveness.

You will support efforts to structure, process, and analyze large multimodal datasets-including heart rate, EEG, eye tracking, and recorded speech-using signal processing, statistical modeling, and machine learning techniques. This includes contributing to both descriptive and predictive modeling pipelines, as well as applying large language models (LLMs) to interpret team communication and detect key performance-related signals.

The position requires strong programming skills, especially in Python, and a working knowledge of data-driven modeling and algorithm development. You'll implement and test code that transforms research-grade algorithms into reproducible, scalable analysis tools. You may also assist in human subject data collection, including sensor setup and experiment execution.

This is an applied research role ideal for early-career professionals who want to work at the intersection of human performance, data science, and machine learning. The ideal candidate is motivated to build tools that help computers interpret human states and interactions in real-world, dynamic settings. You'll have the opportunity to grow your expertise in physiological computing, team cognition, and AI-enabled assessment technologies.

Assist with human subject data collection, including setup and operation of physiological and behavioral sensors (e.g., EEG, heart rate monitors, eye trackers) during experimental sessions.
• Preprocess and clean raw data from multiple sensing modalities, applying techniques such as filtering, synchronization, artifact rejection, and signal quality checks.
• Implement and refine data analysis pipelines using Python and scientific libraries (e.g., NumPy, Pandas, SciPy, Scikit-learn), with a focus on time-series and multimodal data.
• Develop and test machine learning models to predict team performance using physiological, behavioral, and communication data.
• Apply natural language processing (NLP) and large language models (LLMs) to transcribed team communication data to extract meaningful features or behavioral indicators.
• Maintain organized codebases and documentation to support reproducibility and collaboration across the research team.
• Contribute to experimental design and protocol development, especially around data integrity, sensor deployment, and human subject safety/compliance.
• Collaborate closely with senior scientists to translate high-level research questions into implementable technical solutions.
• Summarize and present findings in internal meetings, including visualizations, code outputs, and analysis results to support scientific interpretation and reporting.
• Stay current with relevant tools, libraries, and techniques in data science, physiology, and human performance modeling.

Required Qualifications

* Bachelor's or 2 years or Master's degree in a relevant field (e.g., Biomedical Engineering, Cognitive Science, Computer Science, Psychology, Neuroscience, or related discipline).
* Proficiency in Python programming, with demonstrated experience in scripting for data analysis and working with scientific libraries (e.g., NumPy, Pandas, SciPy, Scikit-learn, Matplotlib).
* Hands-on experience with data analysis, including signal processing (e.g., filtering, artifact rejection, time-series alignment) and/or machine learning model development.
* Familiarity with physiological and behavioral data, such as heart rate, EEG, eye tracking, or voice recordings, especially in human subject research contexts.
* Strong attention to detail and ability to follow protocols for human subject data collection, including managing sensors and recording systems.
* Ability to work collaboratively in a fast-paced research environment, taking direction while contributing technical insight.
* Clear written and verbal communication skills, especially for documenting code, processes, and preliminary findings.

* U.S. citizenship and ability to obtain a clearance in the future

Preferred Qualifications

* Experience with human subject research, including IRB protocols, consent processes, or hands-on data collection in lab or field environments.
* Familiarity with teamwork or communication research, or interest in understanding human performance in applied/military contexts.
* Exposure to large language models (LLMs) or natural language processing (NLP), especially in applying models to communication analysis.
* Experience working with multimodal data or time-synchronized datasets.
* Knowledge of experiment design tools (e.g., PsychoPy, LabStreamingLayer) or biosignal tools (e.g., BioPac, iMotions, OpenBCI) is a plus.

Additional Notes

* This is a junior-level position ideal for someone with a strong foundation in coding and data analysis who is eager to gain experience in high-impact human performance research.
* You will receive mentorship from a team of senior scientists with expertise in cognitive modeling, machine learning, and physiology.