Research Data & Information Scientist/Computer Engineer (AI/ML & Edge Systems)

Rome, NYTackle open research problems in model robustness, streaming data, and low-power compute for autonomous mission systems by joining our team as a Machine Learning Research Scientist or Engineer for Edge AI & Drift Detection!DR-02: $75,484 - $118,528, The Information and Spectrum Warfare Directorate (RF), Information Systems Division (RFC) seeks to hire a mid-level, DR-02 (GS-12/13 or equivalent) Data & Information Scientist / Computer Engineer in Rome, New York to research, prototype, test, and demonstrate cutting-edge Artificial Intelligence and Machine Learning (AI/ML) capabilities, edge software architectures, and automated data pipelines. This role focuses on developing resilient AI solutions capable of detecting data and concept drift in real time on resource-constrained embedded systems, directly supporting tactical decision advantage in contested environments.

Position duties include, but are not limited to:

• Pioneer AI/ML Drift Detection & Model Reliability: Formulate, implement, and benchmark algorithms to detect covariate shift, concept drift, and statistical anomalies in real-time, unstructured data streams without requiring immediate ground-truth labels.
• Architect Low SWaP-C Edge Processing Pipelines: Design, prototype, and optimize lightweight, containerized ML inference and monitoring pipelines for heterogeneous embedded platforms (e.g., Jetson, embedded GPUs, SoC FPGAs) adhering to strict compute, memory, and thermal constraints.
• Autonomous & Adaptive Learning: Research and demonstrate semi-supervised learning, active learning, and lightweight continuous retraining routines that enable edge systems to dynamically adapt to changing battlespace conditions across disadvantaged communication networks.
• Engineer Agentic AI Architectures & C2 Orchestration: Research, develop, and evaluate autonomous multi-agent systems, goal-oriented agent workflows, and orchestration frameworks (e.g., hierarchical task networks, tool-augmented LLMs, consensus-based agent swarms) to automate distributed information routing, course-of-action generation, and real-time operational C2 decision support.
• Integrate Multimodal Sensor & Data Pipelines: Develop software systems that ingest, synchronize, and fuse disparate sensor feeds (EO/IR, radar, telemetry, mission communications) using advanced architectures (such as CNNs, GNNs, and transformers) to enable automated processing and rapid kill-web closure.
• Manage Demonstrations & Technical Transition: Plan and execute laboratory experiments, synthetic testbeds, and field exercises under simulated contested conditions; prepares technical briefings, reports, and publications for program offices, warfighters, and academic/industry partners.

Information Science, Artificial Intelligence (AI), Computer Engineering, Machine Learning, Artificial Intelligence (AI), Low Power, Scientific Research, Testing, RFC, Data Management, * US Citizenship.

• Ability to obtain/maintain a Top Secret clearance as a condition of employment.
• Males must be registered for Selective Service, see www.sss.gov.
• This is a drug testing designated position. The incumbent will be subject to random testing.
• Applicants must be able to meet the OPM Qualification Standards of the position being filled: possess a professional science or engineering (S&E) degree, in a relevant technical field, from an accredited (or ABET accredited for engineering) academic institution.
• Applicants must have at least one (1) full year of specialized experience at the next lower grade/band level (DR-01/GS-11 or equivalent). Specialized experience includes: Conducting research, design, and prototyping of machine learning (ML) models and statistical data analysis pipelines, developing software utilizing deep learning architectures (e.g., CNNs, GNNs, transformers) and modern programming languages (e.g., Python, C/C++). Deploying, optimizing, or benchmarking software pipelines on embedded systems or hardware-constrained compute platforms.
• This is an Acquisition Professional Development Program (APDP) position requiring Level/Tier 2 (Practitioner) certification in the Engineering & Technical Management stall. Applicants must list all completed APDP certifications on resume. Selectee will have 5 years to meet the APDP certification requirements of the position., * Master’s or PhD degree in Computer Engineering, Computer Science, Data Science, Electrical Engineering, or Applied Mathematics.
• Specific research experience in AI/ML reliability, out-of-distribution (OOD) detection, statistical process control, or drift detection metrics (e.g., KL divergence, Wasserstein distance, Maximum Mean Discrepancy).
• 3+ years of experience in designing, optimizing, and deploying containerized ML software (Docker, Podman, ONNX Runtime, TensorRT) onto low Size, Weight, Power, and Cost (SWaP-C) embedded devices.
• Understanding of military operational concepts such as Agile Combat Employment (ACE), Long-Range Kill Webs (LRKW), Joint All-Domain Command and Control (JADC2), and operations in Contested, Degraded, and Operationally-Limited (CDO-L) environments.
• Proficiency with multimodal sensor data representation, sparse data encodings, active learning, or graph neural networks.
• Demonstrated ability to collaborate across multidisciplinary civilian, military, academic, and industry partner teams.
• Strong written and oral technical communication skills, including a track record of authoring technical reports, briefings, or peer-reviewed papers.