Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing, deploying, and optimising scalable machine learning systems with an accent on end-to-end ML lifecycle from data exploration to production deployment. Focus on building data pipelines, integrating models into production environments, and working with sensitive data in secure SCIF environments.

Location: Hybrid (~1 day per week in-office) in Washington, DC (or other US locations like San Francisco, CA; Denver, CO; Boston, MA; New York City, NY); remainder remote. Active TS/SCI clearance required and willingness to work in SCIF.

Salary: $160,000 – $210,000 depending on experience

Company

Fast-growing AI and analytics software company helping government and enterprise organizations transform complex data into clear, actionable insights.

What you will do

• Design, deploy, and optimise scalable machine learning systems
• Own the end-to-end ML lifecycle, from data exploration to production deployment
• Build data pipelines and integrate models into production environments
• Work with sensitive data in secure (SCIF) environments
• Collaborate with cross-functional teams

Requirements

• Active TS/SCI clearance and willingness to work within a SCIF
• 3+ years’ experience building and deploying ML models in production
• Strong Python skills and experience with ML/data stack (pandas, NumPy, scikit-learn, PyTorch)
• Experience with data pipelines, MLOps, and production systems
• Familiarity with Docker/Kubernetes, Git, and SQL/NoSQL databases
• Strong problem-solving skills

Culture & Benefits

• Comprehensive benefits including full health coverage
• Flexible PTO
• Opportunity to work on high-impact, mission-critical AI problems