Hybrid Machine Learning Research Scientist – Frontier Lab

at Carnegie Mellon University

• Job title: Machine Learning Research Scientist – Frontier Lab
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Python, PyTorch, Tensorflow
• Location requirements: Hybrid, Arlington, United States

About the role

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

Responsibilities

• 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

• 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

• Employee benefits
• Competitive salary
• Flexible work arrangements
• Professional development opportunities