Bachelor's degree in Computer Science, AI, or related field (or equivalent experience).
12+ years of software engineering experience, focusing on machine learning or NLP.
Expertise in deep learning frameworks like TensorFlow, PyTorch, or MXNet.
Proficient in programming languages such as Python, C++, or Java.
Solid understanding of LLM architectures and training techniques.
Familiarity with cloud platforms and their ML services.
Responsibilities
Develop, deploy, and maintain AI/ML software solutions.
Support training, hosting, and optimization of large language models (LLMs).
Troubleshoot performance issues and enhance system reliability.
Collaborate with technical teams to integrate AI/ML capabilities.
Apply software engineering best practices throughout the development lifecycle.
Benefits
Opportunity to work on cutting-edge AI/ML technologies.
Collaborative environment with cross-functional teams.
Access to advanced tools and resources for professional growth.
Engagement in meaningful projects with national security implications.
Full Job Description
Senior AI/ML Software Engineer (TS/SCI with Polygraph)
Responsibilities:
Develop, deploy, and maintain AI/ML software solutions.
Support the training, hosting, and optimization of LLMs.
Troubleshoot performance issues and improve system reliability.
Collaborate with technical teams to integrate AI/ML capabilities into existing environments.
Apply software engineering best practices throughout the development lifecycle.
Requirements:
Must have an active TS/SCI clearance with polygraph.
Bachelor's degree in Computer Science, Artificial Intelligence, or a related field. An additional 4 years of experience may substitute for a Bachelor's degree.
12+ years of experience in software engineering, with a focus on machine learning or natural language processing.
Degree in Computer Science, Artificial Intelligence, or a related field.
Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
Proficiency in programming languages such as Python, C++, or Java.
Solid understanding of LLM architectures, training techniques, and evaluation methodologies.
Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services.
Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment.
Excellent problem-solving and debugging skills.
Strong communication and collaboration abilities to work effectively with cross-functional teams.
