AI/ML Engineer

540
Arlington, VA, United States
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Amazon Web Services Application Frameworks Automation of Tests Microsoft Azure Cloud Computing Continuous Integration Distributed Computing Environment Python (Programming Language) Machine Learning Tensorflow
+22 more
Azure Machine Learning Software Engineering Management of Software Versions Google Cloud Feature Engineering Retrieval-Augmented Generation Delivery Pipeline Large Language Models Model Validation Generative AI Containerization Kubernetes Infrastructure Automation Frameworks Information Technology Performance Monitor Data Management Machine Learning Operations Api Design Software Version Control Data Pipelines Docker Microservices

Job description

540 is seeking an AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and infrastructure that enable teams to develop, deploy, monitor, and scale models supporting complex defense missions.

Working with software engineers, data engineers, data scientists, cybersecurity teams, and mission stakeholders, you will build reusable ML capabilities and automated pipelines using modern software engineering and MLOps practices. The ideal candidate enjoys solving complex engineering challenges and building secure, reliable AI/ML systems that directly support mission outcomes., Design, build, and maintain AI/ML services, products, and lifecycle capabilities supporting WDP Develop automated pipelines for model training, validation, testing, deployment, and monitoring Create reusable frameworks, libraries, and shared components that accelerate AI/ML development Build model-serving capabilities supporting secure, scalable, and reliable batch or real-time inference Implement MLOps practices using CI/CD, infrastructure as code, automated testing, and source control Develop model monitoring, performance tracking, drift detection, and operational health capabilities Support model explainability, reproducibility, governance, and lifecycle traceability Manage model versions, artifacts, datasets, and feature-engineering workflows Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost efficiency Collaborate with data engineers and data scientists to prepare data and operationalize models Partner with cybersecurity teams to implement security, access-control, auditing, and governance requirements Troubleshoot issues spanning models, applications, data pipelines, infrastructure, and production services Document AI/ML architectures, engineering processes, and operational procedures

Requirements

Citizenship & Clearance Requirement: Per client requirements, candidates must be U.S. Citizens with an active DoW Secret (or higher) clearance Education Requirement: Bachelor’s degree in Computer Science, Engineering, or a related technical field preferred; equivalent combinations of education and relevant experience will be considered 540 Internal Thrive Level: Software Engineer II or III, 4+ years of relevant AI/ML engineering, software engineering, or data science experience Experience developing and deploying production-grade AI or machine learning systems Proficiency with Python and commonly used AI/ML frameworks Experience building automated model training, validation, deployment, and monitoring pipelines Experience with MLOps platforms, practices, and tools Experience deploying models in cloud-based or containerized environments Experience developing APIs, microservices, or model-serving capabilities for batch or real-time inference Understanding of model evaluation, performance monitoring, drift detection, explainability, and governance Experience with Docker, Kubernetes, or similar containerization and orchestration technologies Experience with CI/CD, infrastructure as code, automated testing, and source control Experience working within AWS, Azure, or Google Cloud Familiarity with data pipelines, feature engineering, distributed data processing, and data versioning Ability to troubleshoot issues across applications, infrastructure, data, and machine learning systems Strong communication and collaboration skills, including the ability to document and explain technical decisions

NICE TO HAVE

Experience supporting DoW, federal, Advana, or other enterprise AI/ML and data platforms Experience with AWS SageMaker or comparable cloud AI/ML platforms Experience with MLflow, Kubeflow, Airflow, Argo Workflows, Ray, Feast, or similar tools Experience building AI/ML solutions in secure, regulated, classified, or mission-critical environments Familiarity with large language models, generative AI, retrieval-augmented generation, or foundation-model operations Experience implementing responsible AI, model-risk-management, or AI-governance practices Currently holds, or is willing to obtain within 30 days of employment, an approved certification such as CCSP, CFR, FITSP-M, GSEC, Security+, or SSCP

Benefits & conditions

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)

540’s policy is to provide equal employment opportunity to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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