About this opportunity
DataJobs lists this Machine Learning Engineer /Development Team Lead opportunity in chantilly, Virginia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Ad hoc Research builds AI-driven defense and intelligence capabilities on the DarkStax™ platform, and this role blends hands-on machine learning engineering with day-to-day technical leadership. You will help translate program objectives into executable delivery plans, guide teams from prototype through program use, and support the secure integration of ML capabilities into mission systems.
What you’ll do
Lead day-to-day technical execution for a multidisciplinary development team, including work planning, technical decision-making, 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 providing stakeholders delivery progress updates.
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 results to operational needs.
Build reproducible ML pipelines for data preparation, training, testing, versioning, deployment, and monitoring.
Integrate models into secure applications, services, APIs, and mission systems while maintaining reliability , scalability , and traceability .
Evaluate robustness, failure modes, and vulnerability to adversarial conditions, with focus on cyber, adversarial AI, or communications use cases.
Mentor engineers and data scientists, establish practical development standards, and improve both technical execution and Agile practices.
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.
7 to 10 years of relevant experience in ML 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 ML solutions using reinforcement learning, neural networks, deep learning, computer vision, or related techniques.
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 working knowledge of common ML 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 automated testing, CI/CD , containers, and deployment workflows.
Ability to translate mission and user needs into a prioritized backlog, measurable technical objectives, and incremental releases.
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
Preferred 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, type, and clearance
Location: Chantilly, VA (onsite) (Chantilly, VA 20153 required)
Work type: Full-time, in person; some travel required
Compensation: USD 150,000 per year (from $150,000.00 per year)
Security clearance: Top Secret (required)
Alternate area indicated: Chantilly, VA / Washington, DC metro region, or Plano, TX
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Worksite address
chantilly, VA, 22021, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.