Machine Learning (ML) Engineer

About the role

WWC Global, an operating firm of Command Holdings, is seeking a Machine Learning (ML) Engineer to support USSOCOM's mission to transform the SOF Enterprise into a data-centric organization through the application of scientific methods, algorithms, processes, and systems to extract actionable insights and knowledge from both structured and unstructured data.

Responsibilities

• Designing, developing, deploying, and maintaining machine learning models and AI-enabled systems that support SOF Enterprise data analysis, operational planning, and decision advantage.
• Developing AI/ML algorithms and models including those designed for Natural Language Processing (NLP), computer vision, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and decision-making that learn from data to identify patterns and improve performance over time.
• Building and managing end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Conducting AI/ML modeling and simulation efforts to create models that analyze data, recognize patterns, and make predictions, and using those models to simulate real-world scenarios to test various outcomes without real-world risk.
• Implementing MLOps practices to ensure scalable, repeatable, and auditable model development and deployment workflows.
• Conducting suitability and feasibility assessments to confirm AI/ML is the appropriate tool for a given task and establishing clear requirements and fully specified tasks prior to development.
• Ensuring all LLM/RAG experimentation and model development adhere to mandatory security and data governance requirements defined by Federal, DoW, and SOCOM policies.
• Demonstrating capabilities via robust campaigns of learning.
• Supporting the establishment of clear pathways to adopt capabilities deemed successful after rigorous testing to ensure sustainment and wide-scale adoption.
• Identifying and mitigating operational environment constraints, such as limited bandwidth at the tactical edge and contested environments early in the development process.
• Utilizing appropriate code share repositories (e.g., GitHub) for all development activities.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related technical field.
• Minimum of five (5) years of experience in machine learning engineering, data science, or a related technical discipline, including hands-on experience designing, training, deploying, and monitoring ML models in cloud or hybrid production environments.
• Current, active TS/SCI security clearance.
• Outstanding communication skills, influencing abilities, and client focus.
• Professional proficiency in English is required.
• Demonstrated proficiency in using all Microsoft Office applications.
• Ability to access federal facilities in compliance with Real ID.

Preferred Requirements

• Master's degree or PhD in Machine Learning, Computer Science, Artificial Intelligence, Applied Mathematics, or a related field.
• Experience working in DoD or Intelligence Community environments.
• Experience developing and deploying AI/ML capabilities in support of SOF or other warfighting organizations.
• Experience with LLM/RAG development and GenAI operationalization in classified or restricted environments.
• Experience conducting AI/ML experimentation and multi-lateral exercises to validate model performance against high-impact use cases.
• Experience with low-bandwidth and Disconnected, Intermittent, and Limited (DIL) environment constraints.
• One or more of the following certifications: Databricks Certified Machine Learning Professional, AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate, or equivalent AI/ML platform certification.

Benefits

• Health, Dental, and Vision Insurance
• Flexible Spending Accounts
• Life and Disability Insurance
• 401(k)
• Paid Time Off
• Paid Holidays
• Employee Assistance Program
• Pet Insurance