Machine Learning (ML) Engineer
On-siteTampa, Florida, United States
Job Summary
Design, develop, and deploy machine learning models and AI-enabled systems for SOF Enterprise data analysis, including NLP, computer vision, and Large Language Models. Build end-to-end ML pipelines covering data ingestion, feature engineering, training, validation, and monitoring while implementing MLOps practices for scalable workflows. Conduct suitability assessments, simulate real-world scenarios to test outcomes, and identify operational constraints like limited bandwidth. Collaborate with stakeholders to demonstrate capabilities and establish pathways for successful capability adoption. Ensure all development adheres to Federal, DoD, and SOCOM security and data governance requirements. Utilize code share repositories for all development activities. This contingent contract supports USSOCOM's mission to transform the SOF Enterprise into a data-centric organization.
Required Qualifications
- 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
- Applicants must be currently authorized to work in the United States on a full-time basis
- WWC Global will not sponsor applicants for work visas for this position
Desired Qualifications
- 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: 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
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