Director, Decision Science AI/ML Engineering & Ops
Overview
Lead the Science Factory to build scalable AI-powered decision platforms. Own the technical backbone for deploying ensembled models and custom algorithms into SaaS products. Drive AI/MLOps as a product to accelerate speed-to-market and improve model reusability.
What You'll Do11
- 1Develop and maintain a vision for a high-performing AI/ML engineering team
- 2Architect repeatable MLOps practices across the portfolio
- 3Define AI/ML engineering skill mix and career paths
- 4Create reusable building blocks for scientists and modelers
- 5Design pattern definitions for standardized algorithmic guardrails
- 6Partner with Decision Science teams to engineer scalable batch services
- 7Champion production-first culture with automated testing and monitoring
- 8Identify and resolve technical debt in ML pipelines
- 9Maintain and modernize complex production ecosystems
- 10Ensure explainability and responsible AI principles by design
- 11Drive operational excellence through unified metrics and dashboards
Requirements10
- 112+ years of related experience
- 2Prior experience leading decision scientists and/or ML engineers to production
- 3Strong statistical and modeling fluency to collaborate with scientists
- 4Proficiency with Python R SQL
- 5Experience designing complex algorithms for performance and scalability
- 6Familiarity with AWS infrastructure and services
- 7Master’s degree in Computer Science or related field
- 8Experience with genAI and emerging design patterns
- 9Knowledge of containerization and CI/CD practices
- 10Demonstrated leadership in cross-functional matrixed environments
Salary Insight
$218 - $292k per year
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