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What We Do At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering challenges related to building, deploying, and sustaining AI-enabled systems for high-impact government missions. The Frontier Lab advances AI engineering and transitions frontier AI capabilities to government stakeholders through applied research, rapid prototyping, short-cycle TEVV, and technical advisory. Position Summary As a Senior Machine Learning Research Scientist in the Frontier Lab, you will serve as a senior individual contributor and technical leader, shaping and executing applied research and prototype capability development for government and Do W missions. This role spans the research-engineering spectrum: some SR MLRS hires may lean more research-heavy and others more engineering-heavy, but successful candidates collaborate effectively across both. You will operate with high autonomy, represent technical work with customers and stakeholders, and help guide Frontier Lab research direction-while remaining hands-on in development, evaluation, and delivery. Your work may span Frontier Lab focus areas such as: * Agentic AI for mission workflows (e.g., planning, analysis, decision support) where autonomous and human-guided agents interact with tools, data systems, and operators. * AI test, evaluation, verification, and validation (TEVV) to improve confidence in performance, robustness, uncertainty, and trustworthiness of ML-enabled systems. * Mission-tailored language models, including techniques to improve accuracy and reliability, reduce hallucinations, and integrate structured knowledge for operational tasks. * Mission modalities and multimodal learning, including sensor fusion and learning under noisy, sparse, or constrained data conditions (including synthetic data and weakly-/self-supervised approaches). * AI at the tactical edge, enabling capability under constrained compute/connectivity through efficient inference, compression, rapid adaptation, and update/redeploy patterns. Key Responsibilities / Duties Senior MLRS staff are expected to operate with a high degree of autonomy and technical ownership while remaining hands-on in development, evaluation, and delivery. * Mission-context execution : Execute work within the operational context-understanding users, workflows, constraints, success criteria, and outcomes-so technical decisions are grounded in real mission needs. * Technical leadership / Tech lead : Lead technical execution by defining technical tasking, sequencing work into realistic milestones, maintaining delivery quality, and delegating appropriately across the team. * Applied research and prototyping : Design and run studies, build convincing prototypes and reference implementations, and produce evidence-backed insights that can be matured and transitioned into operational settings. * Evaluation, assurance, and evidence : Establish credible evaluation strategies and test pipelines that assess performance, robustness, reliability, and trustworthiness in mission-representative scenarios. * Customer-facing technical ownership : Serve as the primary technical interface when appropriate ; translate mission goals into measurable technical outcomes; communicate progress, decisions, and risks clearly to stakeholders. * Mentorship and talent development : Proactively mentor junior staff and teammates, raising the bar for research rigor, engineering practice, and delivery habits across project teams. * State-of-the-art awareness and agenda shaping : 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. * Self-direction and time management : Manage multiple priorities effectively, sustain steady execution cadence, and resolve blockers with minimal oversight. * Community building (internal and external) : 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. 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
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
Salary
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