At the SEI’s Enabling Edge Intelligence (E2I) team, we bridge the gap between breakthrough edge AI research and operational, real-world deployment. Our multi-disciplinary team of software engineers, researchers, and data scientists designs and optimizes intelligent edge systems for resource-constrained environments where reliability, safety, and performance are primary drivers. We focus on three core areas:

Evolving Systems for Next-Gen AI: Pioneering methods to integrate emerging paradigms like small language models (SLMs), agentic AI, and hardware-aware runtime optimization. Seamless Cloud-to-Tactical Integration: Driving effective deployment of intelligent capabilities across the full compute continuum—from enterprise cloud down to the tactical edge. Mission-Critical Infrastructure: Architecting resilient capabilities and infrastructure that keep edge operations running reliably in real-world scenarios.

Position Summary:

We are seeking a visionary an Edge AI Research Scientist to develop, mature, prototype, and transition technology that redefines edge intelligence and delivers tangible impact to critical missions. In this role, you will lead high-visibility research initiatives, striking a balance between solving immediate, real-world customer challenges and pioneering long-term solutions to complex technical bottlenecks. You will serve as a lead technical voice — presenting groundbreaking work to executive stakeholders, defense and industry partners, and top-tier academic communities — while actively advancing our core research agenda in areas such as:

Agentic systems for edge intelligence Software engineering to support edge missions Resource management for edge systems Adaptive systems for mission resilience

As a member of the AI-Native Software Engineering (AISE) Directorate, you will also collaborate within the AISE Lab, directly shaping and mastering state-of-the-art AI-assisted tools and workflows that are actively transforming the modern software engineering lifecycle. Requirements:

Education & Experience: PhD in Computer Science, Software Engineering, Machine Learning, or a related field with 2+ years of experience in edge AI system engineering—or equivalent experience (e.g., 8+ years demonstrated experience in developing and transitioning innovative technical solutions to operational practice). Empirical Research: Proven track record of rigorous empirical research design, experimentation, and quantitative validation. Communication: Exceptional written and oral communication skills, with a proven ability to translate complex research into compelling technical narratives.

Desired Experience, Knowledge, Skills, and Abilities:

Operational Deployment: Practical experience building and deploying edge AI software (or systems with similar hardware/network constraints) into real-world operational environments. Academic Leadership: Proven ability to publish and present research findings at premier software engineering, edge computing, or AI conferences and journals. Research Funding: Track record of crafting, winning, and executing research proposals or securing funding from government agencies or strategic industry partners. Analytical & Interpersonal Leadership: Outstanding analytical capabilities paired with strong interpersonal skills to collaborate effectively across multi-disciplinary teams.

Other Requirements:

Travel: Ability to travel (~10%) to present at top-tier venues including but not limited to conferences, collaborate with sponsors, and attend strategic offsite meetings. Onsite Presence: Willingness and capability to work onsite at the SEI main office in Pittsburgh, PA (5 days/week). Security Clearance: You will be subject to a background investigation and must be able to obtain/maintain a Department of War security clearance.

Carnegie Mellon University staff benefits include a generous 8% 403b contribution and tuition benefits for employees and dependent children.