AI ML with Security Clearance

Seeking a motivated AI/ML Engineer to support the exciting Corporate Discovery Services mission. The AI/ML Engineer will act as the critical bridge between data science and software engineering mission capturing requirements from stakeholders to deliver robust, scalable, and functional innovative prototypes and deploy solutions. Job Responsibilities/Qualifications: Mission Focus: Use Machine Learning Operations (MLOps) set of practices to automate and standardize the lifecycle of machine learning models, from development and training to deployment and monitoring, borrowing principles from DevOps to ensure reliable, efficient, and scalable ML systems in production. Create Machine Learning, Generative AI Large Language Models (LLM), Retrieval Augmented Generation (RAG), and Agentic AI AI/ML pipelines. Technical Proficiency: Proficiency in Python with TensorFlow, PyTorch, Scikit-learn, Keras, PySpark, vLLM, and NVIDIA CUDA (Compute Unified Device Architecture) libraries. Strong grasp of version control (GitLab), Continuous Integration/Continuous Deployment (GitLab CI/CD), and containerization (Docker, Kubernetes). Required Qualifications: Bachelor's degree plus 11-years of relevant experience or equivalent. Desirable Skills: MLOps
AWS SageMaker
AWS Bedrock
Gambit
Hub
Jira
Confluence
Docker Hub

Seeking a motivated AI/ML Engineer to support the exciting Corporate Discovery Services mission. The AI/ML Engineer will act as the critical bridge between data science and software engineering mission capturing requirements from stakeholders to deliver robust, scalable, and functional innovative prototypes and deploy solutions. Job Responsibilities/Qualifications: Mission Focus: Use Machine Learning Operations (MLOps) set of practices to automate and standardize the lifecycle of machine learning models, from development and training to deployment and monitoring, borrowing principles from DevOps to ensure reliable, efficient, and scalable ML systems in production. Create Machine Learning, Generative AI Large Language Models (LLM), Retrieval Augmented Generation (RAG), and Agentic AI AI/ML pipelines. Technical Proficiency: Proficiency in Python with TensorFlow, PyTorch, Scikit-learn, Keras, PySpark, vLLM, and NVIDIA CUDA (Compute Unified Device Architecture) libraries. Strong grasp of version control (GitLab), Continuous Integration/Continuous Deployment (GitLab CI/CD), and containerization (Docker, Kubernetes). Required Qualifications: Bachelor's degree plus 11-years of relevant experience or equivalent. Desirable Skills: MLOps
AWS SageMaker
AWS Bedrock
Gambit
Hub
Jira
Confluence
Docker Hub

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