Machine Learning Engineer /Development Team Lead

Ad hoc Research (AHR) is seeking a technical leader to guide day-to-day execution of machine learning capabilities within AHR’s AI-driven defense and intelligence portfolio on the DarkStax platform. This onsite role combines hands-on engineering with Agile leadership, model development, integration, and clear communication of technical tradeoffs to program stakeholders.

Key Responsibilities

• Lead the day-to-day technical execution of a multidisciplinary development team, including work planning, technical decisions, code and model reviews, risk management, and delivery commitments.
• Operate as a Scrum Master and/or Product Owner by facilitating Agile ceremonies, maintaining and prioritizing the backlog, refining acceptance criteria, removing impediments, and communicating delivery progress to stakeholders.
• Design, train, evaluate, and improve machine learning models using reinforcement learning, neural networks, deep learning, and computer vision techniques.
• Define experiment plans, performance measures, validation methods, and data requirements that connect model outcomes to operational needs.
• Develop reproducible ML pipelines for data preparation, training, testing, versioning, deployment, and monitoring.
• Integrate models into secure software applications, services, APIs, and mission systems while maintaining reliability, scalability, and traceability.
• Evaluate model robustness, failure modes, and vulnerability to adversarial conditions, with focus areas including cyber, adversarial AI, and communications use cases.
• Mentor engineers and data scientists, establish practical development standards, and improve technical and Agile practices within the team.
• Collaborate with systems engineers and mission stakeholders to align technical designs, interfaces, demonstrations, and releases with program objectives.
• Present technical approaches, tradeoffs, results, and risks clearly to engineering teams, program leadership, and government customers.

Required Qualifications

• Bachelor’s degree in computer science, machine learning, artificial intelligence, electrical engineering, software engineering, applied mathematics, or a related technical field.
• Seven to ten years of relevant experience in machine learning and software engineering, including experience leading technical teams or workstreams.
• Experience serving as a Scrum Master and/or Product Owner on an Agile development team.
• Hands-on experience developing and evaluating machine learning solutions using reinforcement learning, neural networks, deep learning, and computer vision.
• Experience working in at least one domain: cyber, adversarial AI, or communication systems.
• Software development experience sufficient to build, test, integrate, and maintain production-quality ML capabilities.
• Ability to obtain a TS clearance.
• Strong Python development skills and knowledge of common machine learning frameworks and scientific computing tools.
• Understanding of data preparation, model training, evaluation, experiment tracking, configuration management, and reproducible development practices.
• Ability to design and review software interfaces, APIs, modular services, and integration approaches for ML-enabled systems.
• Experience with MLOps, DevSecOps, automated model testing, model monitoring, or data and model governance.
• Knowledge of software development, automated testing, CI/CD practices, containers, and deployment workflows.
• Ability to translate mission and user needs into a prioritized backlog, measurable technical objectives, and incremental releases.
• Ability to lead technical discussions, make sound tradeoffs, mentor team members, and resolve delivery or integration issues.
• Clear written and verbal communication with technical teams, program leadership, and government stakeholders.

Technologies

• Python
• Reinforcement learning
• Neural networks
• Deep learning
• Computer vision
• MLOps
• DevSecOps
• CI/CD
• Containers

Desired Qualifications

• Active Top Secret (TS) or Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance.
• Prior experience supporting defense or intelligence community customers, including the United States Air Force, United States Space Force, National Reconnaissance Office, National Geospatial-Intelligence Agency, or Defense Intelligence Agency.
• Experience applying model-based systems engineering (MBSE) methods and tools to define requirements, architecture, interfaces, verification, or digital engineering artifacts.
• Experience deploying ML solutions in cloud, edge, constrained, or classified environments.

Location, Travel, and Employment Details

• Work location: Chantilly, VA (onsite) in the Chantilly, VA / Washington, DC metro region or Plano, TX.
• Travel: Some travel is required.
• Job type: Full-time
• Pay: From $150,000.00 per year
• Work location type: In person
• Ability to commute: Chantilly, VA 20153 (Required)

Security Clearance

• Top Secret: Required