Machine Learning Engineer /Development Team Lead
Manager
Application Security
Artificial Intelligence
Data Pipeline
Data Science
DevSecOps
Engineer
Engineering Leader
Lead Machine Learning Engineer
Machine Learning
Machine Learning Engineer
Machine Learning Operations
Machine Vision
Management
Ml Ops
Reinforcement Learning
Risk Management
Software Security
Team Lead
Job Description
The Development Team Lead and Machine Learning Engineer will provide technical leadership and hands-on execution for AHR’s AI-driven defense and intelligence portfolio on the DarkStax™ platform. The role translates program objectives into delivery plans and supports teams from prototype through operational use, with a focus on building, integrating, and evaluating robust AI/ML capabilities.
Core Responsibilities
- Lead day-to-day technical execution of a multidisciplinary development team, including work planning, technical decisions, code and model reviews, risk management, and delivery commitments.
- Act as a Scrum Master and/or Product Owner by facilitating Agile ceremonies, maintaining and prioritizing the backlog, refining acceptance criteria, removing impediments, and updating stakeholders on delivery progress.
- 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 spanning 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 for cyber, adversarial AI, or communications use cases.
- Mentor engineers and data scientists, establish practical development standards, and improve team technical and Agile practices.
- Collaborate with systems engineers and mission stakeholders to align technical designs, interfaces, demonstrations, and releases with program objectives.
- Communicate 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 machine learning solutions using reinforcement learning, neural networks, deep learning, computer vision, or similar methods.
- Experience 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 familiarity with common machine learning frameworks and scientific computing tools.
- Knowledge 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, Employment Type, and Clearance
- Work location: In person (Chantilly, VA onsite), with possible placement in the Chantilly, VA / Washington, DC metro region or Plano, TX.
- Some travel required.
- Job type: Full-time
- Salary: USD 150,000 per year (From $150,000.00 per year)
- Security clearance: Top Secret (Required)
- Ability to commute: Chantilly, VA 20153 (Required)
Education
Bachelor’s degree.