Chief Scientist, AI/ML

Quantum Sky•Reston, VA

1d•$225,000 - $275,000

About The Position

Quantum Sky is hiring a Chief Scientist, AI/ML to set the AI/ML technical bar for Project 137, its applied-research and IP engine. The role spans Project 137’s four pillars—Quantum, Cyber, Decision Advantage, and Digital Platforms & Infrastructure—and reports to the Chief AI Officer. The position is preferred onsite at the Project 137 lab; remote work with regular travel is also considered. The Chief Scientist owns Project 137’s shared AI/ML model layer, including model selection and routing, fine-tuning on mission data, retrieval, and inference at IL5/IL6 and the tactical edge. The role also owns the AI/MLOps and agent harness that moves models and agents from experimentation to cleared production, and the mission evaluation framework used to test performance, safe failure, and resilience under adversarial pressure. The role leads a core team of 2–3 senior scientists and engineers and holds technical authority over AI/ML engineers embedded across the pillars. Responsibilities include setting the AI/ML vision and roadmap; developing LLMs for sensitive and classified mission data; leading computer vision and automatic target recognition; architecting agentic AI systems; building repeatable AI/MLOps workflows; and shaping on-prem AI compute and deployment patterns. The Chief Scientist also guides decisions about retained IP and build, partner, or buy strategies; represents Quantum Sky to government customers and the AI/ML community; supports technical diligence on AI/ML M&A targets; and recruits and develops AI/ML talent. Success is measured by fielded capability, pillar velocity, and IP retained by Quantum Sky. The role requires substantial AI/ML leadership and production delivery experience, with mission, regulated, or other high-consequence environment experience. A PhD, public research or community contributions, active TS/SCI clearance, edge AI experience, adversarial ML experience, and interest in quantum-related methods are desired or preferred qualifications.

Requirements

12 or more years of AI/ML experience, including 5 or more years leading AI/ML teams.
Track record of fielding production AI systems that people depend on, rather than only prototypes and papers.
Hands-on experience fine-tuning, retrieving, evaluating, and optimizing inference for large language models on domain-specific data.
Experience shipping computer vision or automatic target recognition systems involving detection, classification, tracking, or sensor fusion on real-world imagery or signals.
Recent hands-on experience building multi-agent systems, including evaluation and guardrails that make them trustworthy.
Experience building AI/MLOps pipelines, evaluation harnesses, and model lifecycle tools to move models and agents from experimentation to production, including monitoring, drift detection, and rollback.
Experience designing, standing up, or operating on-prem AI compute, including GPU clusters, high-speed interconnect, workload scheduling, and storage; air-gapped or classified settings are particularly relevant.
Experience delivering AI/ML to DoW, IC, or Federal Civilian customers, or in another regulated, high-consequence environment.
Comfort with accreditation, IL5/IL6, and Responsible AI requirements.
Active Secret or TS/SCI clearance preferred; strong candidates may be sponsored.

Nice To Haves

PhD in computer science, electrical engineering, statistics, or a related field.
Peer-reviewed publications at top venues, patents, or widely used open-source work.
Conference talks, public writing, or community leadership recognized in AI/ML.
Active TS/SCI clearance.
Experience fielding models in disconnected, intermittent, or SWaP-constrained environments.
Hands-on experience red-teaming models and agents or defending them against attack.
Interest in where quantum and quantum-inspired methods may help AI/ML, with the judgment to distinguish real results from hype.

Responsibilities

Set and socialize Project 137’s AI/ML roadmap across its four pillars, determining where to lead, follow, or stop investing.
Own the shared AI/ML model layer, including model selection and routing, fine-tuning on mission data, retrieval, and inference optimization.
Lead fine-tuning, distillation, and serving of models on scarce, sensitive, and classified data, including deployment from cloud environments to disconnected and SWaP-constrained settings.
Lead computer vision and automatic target recognition work, including detection, classification, tracking, and sensor exploitation across EO/IR, SAR, RF, and emerging sensor modalities.
Work with the Decision Advantage team to fuse sensor outputs into a decision-grade picture.
Architect multi-agent systems for mission work, including guardrails, auditability, and evaluation needed to support accreditation.
Build and own the mission evaluation harness used by every pillar to test models and agents before release.
Own AI/MLOps pipelines and model lifecycle tooling, including training and evaluation pipelines, model registry, deployment, monitoring, drift detection, and rollback.
Shape and operate the lab’s AI hardware, including GPU clusters, scheduling, storage, and networking, as well as air-gapped and classified deployment patterns.
Determine what workloads run on-prem, in government cloud, or at the edge.
Decide what AI/ML capabilities Quantum Sky builds, partners for, or buys, and shape retained-IP wrappers around frontier and open-weight models.
Lead a core team of 2–3 senior scientists and engineers, and set technical methods, stack, and hiring standards for AI/ML engineers embedded in the pillars.
Recruit, develop, and retain AI/ML talent across Project 137.
Brief program-of-record owners and CIO/CTO/CDAO offices across DoW, IC, and Federal Civilian customers.
Speak at conferences, publish, and represent Quantum Sky in the AI/ML community.
Support technical diligence on AI/ML M&A targets.