AI/ML Research Scientist

Noblis•Reston, VA

9h•Onsite

About The Position

Noblis is seeking an experienced Artificial Intelligence and Machine Learning Systems Research Scientist for a role based in Reston, VA who lives at the intersection of machine learning research, scientific computing and capability development to join our team of technical professionals delivering transformational capabilities to our clients. This role blends original research with real-world collaboration across scientific domains. Noblis and our wholly owned subsidiaries, Noblis ESI and Noblis MSD, take on some of the nation’s toughest challenges, delivering advanced solutions to our customers’ most critical missions. We bring together leading scientific, engineering, and management expertise in a culture grounded in objectivity and collaboration, ensuring our work creates lasting impact across federal missions. We work with a broad range of government agencies in the defense, intelligence, and federal civilian sectors. Learn more and find opportunities at careers.noblis.org At Noblis, we share a passion for excellence and innovation, and we create an environment where people can do meaningful work while maintaining the balance that keeps them energized and fulfilled. We seek out individuals with a natural curiosity and desire to collaborate and learn. We believe our people are our greatest strength, and we consistently seek exceptionally skilled, mission‑driven professionals who care deeply about doing work that enriches lives and makes our nation safer. Noblis has earned numerous workplace awards for our culture, our commitment to employee well‑being, and our dedication to meaningful, impactful work. We also maintain a drug‑free workplace. Remote/hybrid status is subject to change based on Noblis and/or government requirements. All qualified applicants will receive consideration for employment without regard to race, color, ethnicity, sex, age, national origin, religion, physical or mental disability, pregnancy/childbirth and related medical conditions, veteran or military status, or any other characteristics protected by applicable federal, state, or local law. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact us. EEO is the Law | E-Verify | Right to Work

Requirements

US Citizenship is required.
Master's degree with 6+ years of relevant years of experience OR Ph.D. with 4+ years of relevant years of experience.
Degree must be in computational science, computer science, applied mathematics, or a related field.
Demonstrated research record in evolutionary computation, genetic programming, or related ML areas (publications, conference presentations, etc.).
Strong programming skills in Python, C#, C/C++.
Experience with HP computing, including GPU programming in CUDA.
Understanding HP computing paradigms.
Ability to work across disciplines, comfortable translating between domain science and computation.

Nice To Haves

Ability to achieve Secret security clearance
Experience with active learning, symbolic modeling, or ensemble methods.
Familiarity with computer vision, time-series modeling, or reinforcement learning applications.
History of securing external research funding (government grants, SBIR, etc.).
Contributions to open-source ML or scientific computing projects.
Experience mentoring junior researchers or graduate students.
Background in scientific communication and public speaking.
Knowledge of Rust and Fortran would be a plus.

Responsibilities

Design and implement machine learning methods, particularly evolutionary computation, symbolic regression, and active learning, to accelerate scientific discovery across multiple domains.
Develop computational tools that make complex modeling more accessible, interpretable, and efficient.
Pursue research in AI/ML and GenAI model generalization, training efficiency, explainability, and stability.
Collaborate with domain scientists (physics, biology, medical imaging, and others) to apply ML techniques to real problems.
Contribute to open-source software projects and publish in peer-reviewed venues.
Build and maintain high-performance computing workflows, including parallel and distributed architectures.
Develop reinforcement learning and agent-based systems for hypothesis testing and causal discovery.
Contribute to client-facing data science platforms and tools.
Write and support government-funded research proposals.