Software Engineering Institute | Carnegie Mellon University · 1 day ago
Senior Machine Learning Research Scientist - Frontier Lab
Arlington, VA
Full-time
Onsite
Senior Level
5+ years expCarnegie Mellon University's Software Engineering Institute is focused on applied artificial intelligence research for government missions. The Senior Machine Learning Research Scientist will lead applied research and prototype development while collaborating across engineering and research domains to enhance AI capabilities for government stakeholders.
ComputerCyber SecurityEducationSoftware
No H1B
Security Clearance RequiredU.S. Citizen Only
Responsibilities
Execute work within the operational context—understanding users, workflows, constraints, success criteria, and outcomes—so technical decisions are grounded in real mission needs
Lead technical execution by defining technical tasking, sequencing work into realistic milestones, maintaining delivery quality, and delegating appropriately across the team
Design and run studies, build convincing prototypes and reference implementations, and produce evidence-backed insights that can be matured and transitioned into operational settings
Establish credible evaluation strategies and test pipelines that assess performance, robustness, reliability, and trustworthiness in mission-representative scenarios
Serve as the primary technical interface when appropriate; translate mission goals into measurable technical outcomes; communicate progress, decisions, and risks clearly to stakeholders
Proactively mentor junior staff and teammates, raising the bar for research rigor, engineering practice, and delivery habits across project teams
Maintain strong awareness of frontier developments aligned to the Frontier Lab, share insights with the lab, and help shape research directions and future work selection
Manage multiple priorities effectively, sustain steady execution cadence, and resolve blockers with minimal oversight
Build a strong research culture through internal talks, reading groups, and workshops; and engage with external AI/ML communities (professional societies, consortiums, working groups, and conferences) to strengthen collaboration pathways and keep the lab connected to emerging practice
Qualification
Required
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
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
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
Preferred
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
Company
Software Engineering Institute | Carnegie Mellon University
At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice.
501-1000 employees
Funding
Current Stage
Late StageLeadership Team
Paul Nielsen
Director and CEO
Christopher Herr
Senior Engineer/Cybersecurity Exercise Developer and Trainer
Recent News
Seattle TechFlash
2025-06-25
2025-04-30
2025-04-10
Company data provided by crunchbase