540
SeniorSoftwareEngineer(AI/ML)
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer (AI/ML) at 540. Skills: AI/ML, Machine Learning, MLOps, Cloud-native. Design machine learning models. Develop machine learning models”
What You'll Achieve.
Advance mission-critical capabilities; Enhance signal analysis; Enhance anomaly detection; Provide data-driven insights; Enable faster decision-making; Enable accurate decision-making
Industry & Context.
Problem-solving; Troubleshooting
U. S. Citizens, Active DoW clearance, TS/SCI eligibility, Travel up to 25%, Onsite support required
What They're Looking For.
Must Have
8+ years software development, Microservices in containerized environments, Experience with Python, Experience with relational databases, Experience with data warehouses, Ability to produce technical design documentation, Familiarity with MLOps concepts, Ability to design for scalability, Demonstrated ownership, Problem-solving skills, Ability to navigate ambiguity, Excellent communication skills
Nice to Have
Bachelor's Degree in Computer Science, Experience with Google Cloud Platform, Experience with RESTful APIs, Experience with API gateways, Experience with API management platforms, Familiarity with API authentication, Familiarity with API authorization, Experience on U.S. Federal Government programs, Experience in DoW environments
What You'll Do.
Design machine learning models
Develop machine learning models
Deploy models to cloud services
Productionize machine learning models
Productionize data pipelines
Design MLOps at scale
Deploy MLOps at scale
Integrate AI/ML capabilities
Support transactional workloads
Support analytical workloads
Contribute to technical design
Contribute to system architecture
Participate in code reviews
Participate in testing
Participate in troubleshooting
Drive system reliability
Improve system performance
Improve system scalability
Improve system reliability
How You'll Work.
Team & Collaboration
Cross-functional team; Data engineers; Data scientists; Architects; Engineers; Scientists
Communication Scope
Working with stakeholders; Working with clients
Process & Methodology
Agile
Full Job Description
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. 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. Location: 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% Citizenship & Clearance Requirement: Per client requirements, candidates must be U. S. Citizens with an active DoW clearance with TS/SCI eligibility Education Requirement: Bachelor's Degree in Computer Science or related field (preferred) 540 Internal Thrive Level: Senior Software Engineer WHY 540? 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. HOW YOU’LL DRIVE IMPACT Design and develop machine learning models and applications for deployment to cloud-native services Collaborate with data engineers and data scientists to productionize machine learning models and data pipelines Collaborate with a cross-functional team of architects, engineers, and scientists to design and deploy Machine Learning Operations (MLOps) at scale Integrate AI/ML capabilities into production systems (e.g., model inference APIs, decision-su
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