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Maania Consultancy Services

AI/ML Engineer - Secret

Posted a day ago
2-5 years experience
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AI Summary

The AI/ML Engineer will develop and integrate LLM-enabled software, RAG capabilities, and multi-step AI workflows into operational systems. They are responsible for designing inference pipelines, evaluating AI system performance, and documenting technical findings.

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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