Chief AI/ML Engineering & Platform Strategy

United States Digital Space LLC; Denver (NY); On-site; USD 260,000 - 350,000; Full time

Benefits offered by this job

Equity (RSUs)

Competitive base pay

Total rewards program

Job summary

United States Digital Space LLC is seeking a strategic Head of AI/MLE to lead and scale our AI/ML programs across the company. You will unify classical ML and GenAI, guide platform development, and partner with executive teams to drive measurable business value and risk-controlled AI adoption.

You will oversee Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, shaping how AI-native products and internal systems are built for reliability, governance, and impact.

Qualifications

• Proven experience leading applied AI/ML teams and delivering customer-facing software solutions.
• Deep technical expertise across AI/ML systems including GenAI, ML platforms, and production deployment.
• Strong software engineering foundation with systems thinking and reliability focus.

Responsibilities

• Define and lead the AI/ML systems strategy across the company, unifying classical ML and GenAI.
• Manage and grow a broad AI/ML organization including ML Engineering, ML Platform, and risk data science teams.
• Partner with senior leaders to identify AI/ML opportunities that create customer value and business impact.
• Shape product and internal systems to ensure safe, observable, and scalable AI/ML deployments.
• Develop platform capabilities, tooling, guardrails, and self-service features for teams.

Skills

Leadership

AI/ML systems

Software engineering

Executive communication

Cross-functional collaboration

Strategy development

Education

Advanced degree in CS/DS/ML

Job description

United States Digital Space LLC is seeking a strategic Head of AI/MLE to lead and scale our AI/ML programs across the company. You will unify classical ML and GenAI, guide platform development, and partner with executive teams to drive measurable business value and risk-controlled AI adoption.

You will oversee Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, shaping how AI-native products and internal systems are built for reliability, governance, and impact.