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Cordia Resources by Cherry Bekaert

Senior Machine Learning Engineer

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  • US
    United States
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À propos

Job Title:
Senior Machine Learning Engineer - LLMs & Cloud AI Location:
Hybrid (Remote + Onsite as needed) Clearance Requirement:
Must be eligible for Public Trust
About the Role Join a mission-driven team at the forefront of AI innovation in the public sector. We're seeking a Senior Machine Learning Engineer with deep expertise in Large Language Models (LLMs), LangChain, and OpenAI technologies to lead the development of intelligent, secure, and scalable AI systems in a cloud-native environment.
This role is ideal for a seasoned AI professional ready to architect and deploy advanced ML workflows that support federal initiatives and deliver real-world impact.
Key Responsibilities Design, fine-tune, and deploy LLMs (e.g., GPT-4, LLaMA, T5) for generative AI, summarization, classification, and conversational tasks. Build intelligent agent-based applications using LangChain, including tools, chains, memory, and RAG pipelines. Architect and deploy AI/ML systems on AWS (SageMaker, Lambda, Bedrock, Redshift, S3, ECS/EKS). Integrate OpenAI APIs (GPT-4, embeddings, function calling) into secure, compliant federal applications. Develop robust MLOps pipelines using MLflow, SageMaker Pipelines, and Step Functions. Implement and manage vector databases (FAISS, Pinecone, OpenSearch) for embedding-based search. Ensure all implementations meet federal security, privacy, and compliance standards. Experiment with prompt engineering, hyperparameter tuning, and inference optimization. Collaborate with engineering, DevOps, and compliance teams to deploy production-ready AI services. Document architecture and workflows to support transparency and auditability. Stay current with emerging trends in LLMs, LangChain, OpenAI, and AWS AI/ML services. Required Skills and Experience
Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. 8+ years of experience in machine learning and AI system development. Strong background in NLP and transformer-based architectures (GPT-style models). Hands-on experience with LangChain and OpenAI APIs. Proficiency in AWS services (SageMaker, Bedrock, Lambda, S3, Redshift, ECS/EKS). Skilled in Python and libraries such as Hugging Face, PyTorch, TensorFlow, FastAPI, and scikit-learn. Solid understanding of MLOps, CI/CD, containerization, and pipeline automation. Must be eligible to obtain and retain Public Trust clearance. Preferred Qualifications
Experience supporting federal agencies or public sector AI initiatives. Expertise in retrieval-augmented generation (RAG), prompt engineering, and embedding-based search. Familiarity with LangSmith, OpenAI fine-tuning, and multi-agent systems. Experience with Docker, Kubernetes, and scalable containerized services. Knowledge of ethical AI, bias mitigation, and AI governance best practices.

Compétences idéales

  • AWS
  • Lambda
  • United States

Expérience professionnelle

  • Machine Learning
  • NLP
  • DevOps

Compétences linguistiques

  • English
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