AI/ML Engineer - Secret

Maania Consultancy Services

  • Laurel, MD
  • 20 days ago

    Highlights

    Experience with several of the following can strengthen your fit: Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows. D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.

    Numbers & Facts

    LocationLaurel, MD

    Description

    Required Skills:
    • A master’s degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.
    • At least four years of relevant AI/ML experience that includes work with large language models, retrieval-augmented generation, and prompt engineering.
    • Hands-on experience integrating LLM-enabled software and RAG capabilities into applications or workflows.
    • Developing or supporting agentic-AI capabilities and multi-step AI workflows.
    • Designing, building, or supporting inference pipelines.
    • Ability to evaluate AI-enabled capabilities and clearly document findings, design decisions, and results.
    • Testing and documenting AI-enabled software capabilities.
    • Ability to clearly explain your personal technical ownership and contributions.
    • Strong collaboration and technical-communication skills.

    Preferred Background

    Experience with several of the following can strengthen your fit:

    • Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows.
    • Evaluating grounding, reliability, output quality, hallucinations, or other limitations of AI-enabled systems.
    • Integrating AI services with backend APIs or established software applications.
    • Secure software-development lifecycle and DevSecOps practices.
    • OpenShift, Kubernetes, CI/CD, or containerized application delivery.
    • Secure, restricted, disconnected, on-premises, or classified development environments.
    • Defense, government, aerospace, mission-planning, or other regulated environments.
    • Collaboration with software-engineering, cybersecurity, platform, and customer-facing technical teams.

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