🛠 Tech Stack

💼 About This Role

You'll design and mature Raft's ML platform and MLOps infrastructure for the Department of Defense. You'll build secure, scalable deployment pipelines and manage GPU-enabled Kubernetes clusters to support mission-critical AI systems. This role offers the chance to work on cutting-edge defense technology with high-impact problem-solving.

🎯 What You'll Do

• Design and maintain secure, scalable MLOps infrastructure and deployment pipelines
• Manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Build CI/CD workflows for ML services and model artifacts
• Partner with ML engineers to move models from experimentation to production

📋 Requirements

• 7+ years of experience in software engineering, platform engineering, or MLOps
• 5+ years of experience with Docker and Kubernetes in production
• Experience building and maintaining ML platforms or infrastructure
• Ability to obtain and maintain Top Secret clearance

✨ Nice to Have

• Experience with Triton Inference Server, KServe, or similar model serving platforms
• Experience with Kubeflow or other Kubernetes-based ML platforms
• Familiarity with Istio or service mesh technologies

🎁 Benefits & Perks

• 🏖️ Flexible work environment
• 💰 Competitive salary
• 📚 Professional development opportunities
• 💻 Remote work options
• 🎯 Impactful mission

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min

🚩 Heads Up

• Requires Security+ certification within 90 days, which may be an additional burden
• Demands ability to obtain Top Secret clearance, which can be a lengthy process
• Mentions both on-prem and edge deployment, indicating complex environments