Senior Software Engineer (AI/ML)

Requirements

• Experience with Google Cloud Platform (GCP) or similar cloud environments
• Experience designing and consuming RESTful APIs
• Experience with API gateways and API management platforms, such as Google Apigee
• Familiarity with API authentication and authorization (PKI, OAuth2, JWT, LDAP, SAML, etc.)
• Experience working on U.S. Federal Government programs, particularly DoD environments
• Google Cloud Professional-level certifications
• BENEFITS & PERKS
• Flexible PTO + all Federal holidays off
• Health, dental and vision insurance plans
• Flexible Spending Account (FSA)
• 401k with employer match
• Company-sponsored life insurance, short- and long-term disability
• Professional development (training, certifications, conferences)
• Paid cloud developer accounts
• Referral bonuses
• HQ office perks (parking / metro reimbursement, nitro coffee & lunches)
• Annual social events (540 Week, hackathon, charity golf tournament, etc.)
• Access to 540's Washington Capitals & Nationals tickets
• EQUAL EMPLOYMENT OPPORTUNITY (EEO)
• This policy applies to all terms and conditions of employment, including recr

Benefits

Additional Information

540 is seeking a Senior Software Engineer (AI/ML) to support our partnership with Google and the Department of Defense 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 (Patrick Space Force Base). Primarily onsite, up to 5 days/week Citizenship & Clearance Requirement : Per client requirements, candidates must be U.S. Citizens with an active DoD 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-support features, anomaly detection workflows) Design and optimize data models and persistence layers to support both transactional and analytical workloads Enable intelligent application behavior by delivering AI and ML features to user-facing applications Contribute to technical design documentation and system architecture artifacts Lead or participate in code reviews, testing, and troubleshooting to ensure high-quality software Drive system reliability through robust testing Improve system performance, scalability, and reliability as the platform evolves REQUIRED SKILLS & EXPERIENCE 8+ years of professional software development experience Experience developing microservices in containerized environments Experience with, or a strong conceptual understanding of, LLM-based applications, RAG pipelines, and AI-driven decision systems Experience with Python Experience working with relational databases and data warehouses Experience integrating AI/ML capabilities into applications (e.g., working with model inference APIs, ML pipelines, or data-driven features) Ability to produce technical design documentation (system diagrams, architecture artifacts) Familiarity with MLOps concepts (model deployment, monitoring, versioning) Ability to design with future scalability and platform evolution in mind Demonstrated ownership and ability to drive work from concept to production Strong problem-solving skills and ability to navigate ambiguity Excellent communication skills, including working directly with stakeholders or clients

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