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AI Engineer

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BLN24

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Location:
United States , McLean

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Category:
IT - Software Development

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Contract Type:
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Salary:

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Job Description:

The AI Engineer will design, develop, and deploy artificial intelligence and machine learning solutions to support high-impact federal programs focused on intelligent automation, data quality, and predictive analytics. This role combines deep technical expertise in ML engineering with strong collaboration skills to build scalable, production-ready models integrated into cloud-native and API-driven environments.

Job Responsibility:

  • Design and implement machine learning models and AI solutions, including natural language processing (NLP), large language models (LLMs), and deep learning architectures
  • Build end-to-end ML pipelines from data ingestion and preprocessing through model training, evaluation, and production deployment
  • Operationalize models using MLOps practices and tools such as MLflow, Docker, and cloud-native services
  • Deploy models into production environments using SageMaker, Vertex AI, TorchServe, FastAPI, or similar deployment frameworks
  • Collaborate with software engineers, DevOps teams, and product owners to ensure integration of models into applications and workflows
  • Monitor model performance, retraining schedules, and observability metrics to ensure reliability and compliance
  • Translate complex data and model outputs into actionable insights for technical and non-technical stakeholders
  • Participate in Agile ceremonies, code reviews, and model documentation to support collaboration and transparency

Requirements:

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • Minimum 3 years of experience in software/ML engineering
  • Proven experience leading and delivering end-to-end AI/ML projects in production environments
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
  • Experience building NLP pipelines, working with transformer-based models, or developing applications using LLMs
  • Hands-on knowledge of MLOps tools and practices including MLflow, model versioning, containerization (Docker), and CI/CD for ML
  • Experience deploying models to production using cloud platforms such as AWS SageMaker, GCP Vertex AI, or custom APIs like FastAPI or TorchServe
  • Familiarity with data engineering principles and integration with upstream data pipelines
  • Ability to collaborate across disciplines, mentor junior team members, and communicate technical solutions clearly

Nice to have:

  • Experience with LLM fine-tuning, Retrieval-Augmented Generation (RAG), or generative AI solutions
  • Prior contributions to open-source ML/AI projects or model repositories (e.g., Hugging Face)
  • Experience applying AI in regulated domains such as finance, healthcare, or government
  • Familiarity with model interpretability, fairness, and bias mitigation techniques
  • Exposure to secure AI deployment practices in compliance with federal privacy and governance standards (e.g., FISMA, IRS Pub 1075)
What we offer:
  • Generous medical, dental, and vision plans
  • Opportunity to work in different sectors
  • Flexibility to balance quality work and personal lives
  • Remote working opportunities

Additional Information:

Job Posted:
January 04, 2026

Employment Type:
Fulltime
Work Type:
Remote work
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