Distributed Systems ML Infrastructure Engineer

📋 Description

• Design and implement platform services for workflow orchestration, data ingest, and results
• Implement and operate model gateway and serving services that route invocations to approved managed
• Maintain a documented provider abstraction so the platform runs on AWS-native managed services
• Deploy platform releases into classified host environments, perform data source integration, and
• Verify environment parity after each promotion
• Size and validate the platform against documented workload models, and verify capacity and

🎯 Requirements

• U.S. citizenship and eligibility to obtain and maintain a U.S. security clearance
• 6+ years of experience in distributed systems, platform engineering, infrastructure engineering, or
• Production experience operating Kubernetes and containerized workloads on a major cloud platform
• Experience with managed Kubernetes services such as Amazon EKS or an equivalent platform
• Experience supporting machine learning workloads in production, such as model serving, GPU
• Experience designing, building, or operating distributed services that support reliability

🎁 Benefits

• Medical, Dental & Vision – 100% paid for employees, 75% for dependents
• 401(k) Match – Up to 5% with full vesting after 2 years
• Unlimited PTO – With a required minimum of 15 days off annually
• Fully Remote Setup – Includes up to $3,000 equipment reimbursement
• Continuous Education – Includes up to $500 reimbursement
• Disability & Life Insurance – 100% employer-paid