Machine Learning Engineer

Role Overview

RAZOR is seeking a Machine Learning Engineer to develop, train, and deploy generative AI models across the full ML lifecycle. You will build systems that support federal law enforcement and national security partners, working at the intersection of AI, cybersecurity, and identity technologies.

Key Responsibilities

• Train and fine-tune generative AI models
• Build training pipelines and support data/ML workflows
• Develop evaluation frameworks to assess model quality
• Optimize inference performance
• Integrate models into production systems
• Collaborate with engineering teams on end-to-end delivery
• Document models, processes, and related technical artifacts

Required Qualifications

• 3+ years of ML engineering experience
• Proficiency in Python and PyTorch
• Experience with generative models
• Strong ML fundamentals
• Data pipeline experience
• Familiarity with Linux, Docker, and AWS
• U.S. citizenship

Preferred Qualifications

• Distributed training
• Computer vision
• Experience with LLMs and/or RAG
• Production ML experience

Hybrid Work Location & Schedule

• Location: McLean, VA or Columbia, MD (hybrid)
• On-site presence 2–3 days/week for collaboration; flexibility for remote work
• Monday–Friday; occasional monitoring outside standard hours for extended training jobs

Success Milestones

• 30 days: Learn systems
• 90 days: Deliver models
• 6 months: Production deployment

Compensation & Benefits (Highlights)

• Fully paid medical/dental/vision premiums
• 401(k) with 10% company contribution (Vanguard), vested immediately
• 7 weeks paid time off
• Life and disability insurance; dependent care and health FSA
• Professional development: $5,000/year plus tuition reimbursement
• $200/month communication allowance
• $2,000 technology allowance every two years
• Equity plan and referral/annual/spot bonuses