Senior Machine Learning Research Scientist - Frontier Lab
AI summary of the role
Senior individual contributor and technical leader in the Frontier Lab at SEI's AI Division, conducting applied research and prototyping for government missions.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Lead technical execution by defining tasking, sequencing work into milestones, and maintaining delivery quality.
- Design and run studies, build prototypes and reference implementations, and produce evidence-backed insights for operational settings.
- Establish evaluation strategies and test pipelines for performance, robustness, reliability, and trustworthiness in mission-representative scenarios.
- Serve as primary technical interface with customers, translating mission goals into measurable technical outcomes.
What you’ll bring
- BS in CS, EE, Statistics, or related field with 10 years experience; OR MS with 8 years; OR PhD with 5 years.
- Deep expertise in one or more Frontier Lab-aligned areas (agentic systems, LLM reliability/evaluation, CV evaluation, TEVV pipelines, multimodal learning, edge ML).
- Strong engineering capability to 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.
Technologies
agentic AI · LLM · TEVV · multimodal learning · edge ML · sensor fusion · synthetic data · weakly-supervised learning · self-supervised learning · NeurIPS · ICLR · ICML
Source and classification
Internal deployment & tooling · Evidence for this classification:
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 DoW 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
More from the job description
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 DoW 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 [... source excerpt omitted ...] 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 rea [... source excerpt omitted ...] d 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 al
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