Machine Learning Research Scientist – Frontier Lab

Carnegie Mellon University

Machine Learning Research Scientist conducting applied AI/ML research at SEI. Developing prototype capabilities for government workflows with a focus on mission context.

Posted 4/15/2026full-timeArlington • Pennsylvania, Virginia • 🇺🇸 United StatesSeniorLeadWebsite

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Execute tasks within the mission context, considering users, use cases, operational constraints, and intended outcomes.
Translate sponsor goals into clear technical questions, measurable success criteria, and credible evaluation evidence.
Design and conduct studies grounded in mission needs; form hypotheses, run controlled experiments, analyze results, and produce actionable recommendations.
Build research prototypes, evaluation harnesses, and reference implementations that demonstrate feasibility and generate learning in realistic settings.
Develop and apply evaluation methodologies for ML systems (especially CV and LLMs), including metrics, benchmark design, robustness testing, uncertainty and calibration approaches, and repeatable test pipelines.
Write clear, maintainable code and documentation with a level of engineering discipline proportionate to the intended use.
Plan and deliver work in iterative cycles; manage priorities effectively; communicate status and risks early; and maintain momentum with minimal supervision.
Communicate technical progress and results clearly to technical and non-technical stakeholders through briefings, demos, reports, and recommendations.
Identify opportunities to publish research insights and lessons learned at reputable venues, subject to customer and releasability constraints.
Contribute to technical discussions shaping tasking and delegation, support shared project goals, and provide guidance to junior teammates when appropriate.

Requirements

What you’ll need

BS in Electrical Engineering, Computer Science, Statistics, or related discipline with eight (8) years of experience in hands-on software development; OR MS in the same fields with five (5) years of experience; OR PhD with two (2) years of relevant experience.
Strong foundation in machine learning and statistical learning, including experiment design and evaluation.
Demonstrated ability to implement ML systems in Python using modern ML libraries (e.g., PyTorch / TensorFlow) and common scientific tooling.
Demonstrated ability to communicate technical results clearly in written deliverables and presentations.
Ability to work effectively with ambiguity and deliver results in iterative project cycles with strong self-direction.

Benefits

Comp & perks

Employee benefits
Competitive salary
Flexible work arrangements
Professional development opportunities

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningstatistical learningexperiment designevaluation methodologiesPythonPyTorchTensorFlowmetricsbenchmark designrobustness testing

Soft Skills

communicationself-directionprioritizationtechnical discussionguidanceproblem-solvingadaptabilitycollaborationanalytical thinkingdocumentation