Are you an AI/ML Engineer, Architect, or Developer passionate about applying cutting-edge technologies to national security missions—but don’t see a current opening at ANSER that aligns with your experience?

We’d still love to connect.

At ANSER, we’re always looking to engage with cleared AI/ML professionals who bring both technical expertise and a strong sense of mission. If you're driven to solve complex challenges using artificial intelligence and machine learning—and are comfortable working in secure, classified environments—send us your resume so we can consider you for future opportunities.

 About AI/ML Work at ANSER

As part of ANSER’s growing AI/ML community, you’ll be on the forefront of advising and guiding and developing decision support for the deployment and implementation of intelligent systems in support of high-priority defense and national security initiatives. You’ll help shape the next generation of decision support, automation, and data-driven capabilities, working alongside analysts, system engineers, and government stakeholders.

Most roles are on-site in throughout Northern Virginia and the Washington, D.C. area. Due to the classified nature of the work, remote or hybrid options are typically not available.

 Key Responsibilities May Include but are not limited to:

• Testing, advising and developing guidance and recommendations for the AI solutions and ML models.
• Provide risk assessments for mitigation solutions for AI and ML capabilities related to mission critical needs.
• Providing support for the design, training, and deployment of ML models for applications such as predictive analytics, NLP, computer vision, anomaly detection, and decision support.
• Testing and applying generative AI techniques to enhance simulation, content creation, and mission planning within secure domains.
• Exploring and implementing agentic AI capabilities, including autonomous agents that reason, plan, and act within operational constraints to support human decision-makers.
• Building scalable AI/ML architectures that operate effectively within air-gapped or classified environments.
• Working with structured and unstructured data sources to build pipelines for data ingestion, cleansing, feature extraction, and transformation.
• Collaborating with software developers, data scientists, and mission SMEs to integrate AI/ML solutions into larger operational systems or platforms.
• Evaluating emerging technologies and frameworks for potential use in secure or constrained government environments.
• Preparing technical documentation, model explainability reports, and evaluation metrics tailored for non-technical audiences and decision-makers.

 Ideal Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees (Ph.D., M.S.) are highly desirable.
• 3+ years of experience in AI/ML engineering, processes, data or development roles, preferably within DoD, defense, or federal contracting environments.
• Proficiency in Python and common ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face.
• Experience with generative models (e.g., LLMs, diffusion models) and agent-based architectures or multi-agent systems is highly valued.
• Familiarity with ML ops, containerization (Docker, Kubernetes), and secure deployment strategies.
• Understanding of responsible AI principles, model governance, and algorithm assurance.
• Experience deploying ML models in air-gapped, on-prem, or classified environments is a strong plus.
• Strong problem-solving skills, creativity, and adaptability when working with messy or incomplete real-world data.

 Clearance Requirements:

• Active Secret clearance is required for most roles.
• Top Secret or SCI eligibility is highly desirable, and some positions may require a polygraph.

 If you’re ready to apply AI/ML expertise and experience where it matters most, let’s stay in touch. Submit your resume today and we’ll keep you in mind for future positions that align with your technical background and security clearance.

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