Machine Learning Research Scientist - Frontier Lab

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 test and evaluation, and technical advisory. Position Summary As a Machine Learning Research Scientist in the Frontier Lab, you will conduct applied AI/ML research and develop prototype capabilities that inform and improve real government and DoW workflows. You will execute work in mission contextu2014developing an appreciation for users, operational constraints, and intended outcomesu2014and translate sponsor needs into technically credible approaches and evidence. This role spans the research-engineering spectrum: some MLRS hires may lean more research-heavy and others more engineering-heavy, but successful candidates collaborate effectively across both. Frontier Lab work spans several complementary focus areas, including: + 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 + Mission-context execution: 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. + Applied research and experimentation: Design and conduct studies grounded in mission needs; form hypotheses, run controlled experiments, analyze results, and produce actionable recommendations. + Prototype capability development: Build research prototypes, evaluation harnesses, and reference implementations thatdemonstratefeasibility and generate learning in realistic settings. + Evaluation and assurance (TEVV): 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. + Engineering rigor appropriate to the task: Write clear, maintainable code and documentation with a level of engineering discipline proportionate to the intended use. Emphasize reproducibility and handoff-ready artifacts suitable for downstream integration and operational hardening through formalDevSecOpsprocesses. + Iterative execution, self-direction, and time management: Plan and deliver work in iterative cycles; manage priorities effectively; communicate status and risks early; andmaintainmomentum with minimal supervision. + Customer translation and communication: Communicate technical progress and results clearly to technical and non-technical stakeholders through briefings, demos, reports, and recommendations. + Publication and knowledge dissemination: Identifyopportunities to publish research insights and lessons learned at reputable venues (e.g.,NeurIPS, ICLR, MLCON, etc.), subject to customer and releasability constraints. + Team collaboration: Contribute to technical discussions shaping tasking and delegation, support shared project goals, and provide guidance to junior teammates whenappropriate. Requirements Education / Experience: + BS in Electrical Engineering, Computer Science, Statistics, or related discipline with eight (8) years of experience in hands-on software development; ORMS in the same fields with five (5) years of experience; ORPhD with two (2) years of relevant experience. + Strong foundationin 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. Knowledge, Skills, & Abilities (KSAs) + Communication: Explains technical content clearly; translates between mission problems and technical approaches. + Scientific rigor: Designs sound experiments; recognizes evaluation pitfalls (leakage, confounds, distribution shift). + Practical execution: Balances research quality with timelines and constraints; produces credible evidence and useful prototypes. + Collaboration: Works well in interdisciplinary teams; contributes effectively to shared code and shared evaluation approaches. + Autonomy: Executes independently with low oversight; manages time effectively; escalates risks early and seeks guidance when needed. Desired Experience + Applied ML research and prototyping forreal operationalworkflows, including tool-integrated AI systems and human-in-the-loop settings. + Designing and operating evaluation pipelines for LLMs and/or CV models (benchmarking, regression testing, robustness checks, scenario-based evaluations). + Language model grounding and reliability techniques (structured knowledge integration, RAG, tool use, error analysis). + Learning under constrained/noisy data conditions (synthetic data, programmatic labeling, semi-/self-supervised learning). + Edge-relevant ML (compression, quantization, distillation, efficient inference, rapid adaptation patterns). + Evidence of research output: publications, technical reports, open-source contributions, or applied research artifacts. + Experience working with government/DoWstakeholders or in high-assurance environments. 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 able to obtain and maintain a Department of War security clearance. Joining the CMU team opens the door to an array of exceptional benefits. Benefits eligible ( employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance ( as well as a generous retirement savings program ( with employer contributions. Unlock your potential with tuition benefits (, take well-deserved breaks with ample paid time off ( and observed holidays (, and rest easy with life and accidental death and disability insurance. Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team ( to help navigate childcare needs, fitness center access ( , and much more For a comprehensive overview of the benefits available, explore our Benefits page ( . At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; itu2019s about finding the perfect fit for your professional growth and personal aspirations. Are you interested in an exciting opportunity with an exceptional organization? Apply today Location Arlington, VA, Pittsburgh, PA Job Function Software/Applications Development/Engineering Position Type Staff u2013 Regular Full Time/Part time Full time Pay Basis Salary More Information: + Please visit u201cWhy Carnegie Mellon (u201d 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 ( Interested in a career with Carnegie Mellon University but not finding anything that currently aligns with your interests, background, or experience? Learn how to sign up for Job Alerts (through your candidate profile. If your heart is in your work, come work with us. Carnegie Mellon University isnu2019t just one of the worldu2019s most renowned educational institutions u2013 itu2019s also a hotspot for some of the most talented doers, dreamers, and difference-makers on the planet. When you join our staff, youu2019ll become an important part of our mission to create a healthier, safer, and more just life for all. No matter what your role or location, youu2019ll connect and collaborate with dedicated, passionate colleagues u2013 and youu2019ll have the satisfaction of delivering work that truly matters. We cultivate a vibrant, welcoming environment where everyone is valued and encouraged to contribute and achieve. In addition to competitive benefits and a robust support network, youu2019ll have access to many tools and resources to sharpen your abilities and professional skills, as well as opportunities to engage and share perspectives with a dynamic and inspiring community of uniquely talented staff, faculty, students, and alumni. The future is awaiting your expertise and intellect. Come join the architects of whatu2019s next. Apply now. Learn more about Student Employment (. Please see Faculty Careers. ( For technical assistance, email HR Services () or call 412-268-4600. If you are an individual with a disability and you require assistance with the job application process, please email Equal Opportunity Services () or call 412-268-3930. Prospective Employee Disclosures (

Created: 2026-01-22