Senior Machine Learning Research Scientist - Frontier Lab

Requirements

• Education / Experience
• BS in Computer Science, Electrical Engineering, Statistics, or related field with 10 years of relevant experience; OR MS with 8 years of relevant experience; OR PhD with 5 years of relevant experience.
• Deep expertise in one or more Frontier Lab-aligned areas (agentic systems, LLM reliability/evaluation, CV evaluation, robustness/assurance, TEVV pipelines, multimodal learning, edge ML).
• Strong engineering capability – can build and maintain high-quality prototypes, evaluation infrastructure, and repeatable experimentation workflows.
• Strong written and verbal communication skills; able to represent technical work credibly to senior stakeholders.
• Demonstrated ability to lead technical workstreams and coordinate multi-person execution.
• Knowledge, Skills, & Abilities (KSAs)
• Technical judgment: Makes sound architectural and methodological decisions; balances ambition with mission constraints.
• Customer translation: Converts mission needs into tractable technical plans, measurable success criteria, and credible evaluation evidence.
• Scientific leadership: Maintains rigor; identifies flawed assumptions; improves evaluation quality and research practices.
• Mentorship & influence: Elevates team performance through hands-on guidance and strong technical standards.
• Initiative: Proactively identifies risks/opportunities, proposes new work, and creates alignment without directive management.
• Self-direction and time management: Plans work effectively under ambiguity, maintains execution cadence, and escalates risks early.
• Desired Experience
• Leading applied research projects resulting in effective prototypes, mission-relevant evaluation outcomes, or transitioned methods.
• Publications at strong venues (e.g., NeurIPS / ICLR / ICML, relevant workshops, MLCON), and/or demonstrable impact through applied research artifacts (benchmarks, evaluation suites, open-source, technical reports).
• Designing and operating TEVV efforts including evaluation pipelines, robustness analysis, calibration/uncertainty work, regression suites, and scenario-based evaluation protocols.
• Building agentic capabilities integrated with tools, data systems, and human workflows (decision support, planning, analytic contexts).
• Experience with secure or operational environments and delivery constraints typical of government settings.
• Experience shaping a technical roadmap or research portfolio aligned to sponsor priorities and lab strategy.
• Other Requirements
• Flexible to travel to SEI offices in Pittsburgh, PA and Washington, DC / Arlington, VA, sponsor sites, conferences, and offsite meetings (~10% travel).
• You must be able and willing to work onsite at an SEI office in Pittsburgh, PA or Arlington, VA 5 days per week.
• You will be subject to a background investigation and must be eligible to obtain and maintain a Department of War ) security clearance.
• Location
• Job Function
• Position Type
• Full time/Part time
• Pay Basis
• Please visit “ Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world.
• Click here to view a listing of employee benefits
• Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
• Statement of Assurance

Location

• Job Function
• Position Type
• Full time/Part time
• Pay Basis

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