Senior Software Engineer (AI/ML)

<p>540 is seeking a Senior Software Engineer (AI/ML) to support our partnership with Google and the Department of War in advancing mission-critical capabilities for a global data processing platform. This platform leverages Machine Learning, modern cloud and containerized technologies to ingest, process, and analyze high-volume, time-series data.</p> <p>The system leverages cloud-native infrastructure, while incorporating AI/ML capabilities to enhance signal analysis, anomaly detection, and data-driven insights. Engineers on this team build and scale full-stack features across user interfaces, backend services, and data pipelines that power mission-critical analytics. You’ll play a key role in integrating AI/ML-driven capabilities into production systems, enabling faster, more accurate operational decision-making.</p> <p><strong>Location</strong>: Patrick SFB, FL or Arlington, VA. Candidates should be local to either location. Onsite support may be required based on mission and customer needs. Travel up to 25%<br><strong>Citizenship & Clearance Requirement</strong>: Per client requirements, candidates must be U.S. Citizens with an active DoW clearance with TS/SCI eligibility<br><strong>Education Requirement: </strong>Bachelor's Degree in Computer Science or related field (preferred)<br><strong>540 Internal Thrive Level: </strong>Senior Software Engineer</p> <p><strong>WHY 540?</strong></p> <p>540 is a forward-thinking company that the government turns to in order to #getshitdone. We don’t just talk about innovation – we deliver it. We break down barriers, build impactful technology, and solve mission-critical problems.</p> <p><strong>HOW YOU’LL DRIVE IMPACT</strong></p> <ul> <li>Design and develop machine learning models and applications for deployment to cloud-native services</li> <li>Collaborate with data engineers and data scientists to productionize machine learning models and data pipelines</li> <li>Collaborate with a cross-functional team of architects, engineers, and scientists to design and deploy Machine Learning Operations (MLOps) at scale </li> <li>Integrate AI/ML capabilities into production systems (e.g., model inference APIs, decision-support features, anomaly detection workflows)</li> <li>Design and optimize data models and persistence layers to support both transactional and analytical workloads</li> <li>Enable intelligent application behavior by delivering AI and ML features to user-facing applications</li> <li>Contribute to technical design documentation and system architecture artifacts</li> <li>Lead or participate in code reviews, testing, and troubleshooting to ensure high-quality software</li> <li>Drive system reliability through robust te