Senior Machine Learning Engineer

Role Overview

RAZOR is seeking a Senior Machine Learning Engineer / MLOps Engineer to own the infrastructure supporting AI/ML systems, including pipelines, deployments, and GPU environments.

Key Responsibilities

• Build GPU infrastructure for AI/ML workloads
• Develop CI/CD pipelines to support ML operations
• Automate deployments and infrastructure provisioning
• Optimize inference performance for ML systems
• Implement monitoring for ML and infrastructure health
• Manage infrastructure as code
• Collaborate with ML teams to support end-to-end ML lifecycle needs

Required Qualifications

• 5+ years of MLOps/DevOps experience
• AWS expertise
• Terraform experience
• Docker and GPU knowledge
• Python and/or Bash scripting
• Knowledge of the ML lifecycle

Preferred Qualifications

• Generative AI experience
• Experience with air-gapped environments
• Familiarity with MLflow or Weights & Biases (W&B)
• Federal experience

Location / Work Model

• Remote (U.S.) or McLean, VA (office available for on-site or hybrid)
• Occasional travel to McLean, VA for team onsite/planning and infrastructure work requiring physical access

What Success Looks Like

• 30 days: Understand existing systems
• 90 days: Improve pipelines
• 6 months: Scale infrastructure

Benefits (Highlights)

• Fully paid medical/dental/vision premiums
• 10% company contribution to a Vanguard-sponsored 401(k) (vested immediately)
• Generous PTO (7 weeks)
• Professional development and tuition reimbursement
• Communication allowance and technology allowance
• Employee equity plan