Salary
💰 $152,100 - $203,900 per year
About the role
- Lead development of a standardized, reusable ML platform (AutoML) to support rapid model development for Data Scientists and ensure scalability, flexibility, and integration with enterprise systems
- Drive implementation of robust deployment pipelines, model versioning, testing frameworks, and CI/CD systems to support production-grade ML services
- Establish systems for automated monitoring, drift detection, performance evaluation, and alerting; act as first line of defense for live model health and data quality assurance
- Develop and maintain Feature Mart, enable end-to-end MLOps workflows, and implement robust model monitoring and drift detection
- Assess, pilot, and integrate emerging ML technologies (Generative AI, foundation models, vector databases, LLMOps) to enhance modeling workflows and business capabilities
- Partner with senior leaders across Data Science, Engineering, Product, Legal, and Governance to align objectives, ensure compliance, and scale impact across the organization
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
- 5+ years working in DS/ML engineering or ML platform
- Strong foundation in applied data science, with experience building or supporting ML models in a business context
- Experience with Generative AI or interest in assessing and integrating emerging AI technologies
- Demonstrated expertise in ML Ops, AutoML, and productionizing machine learning at scale
- Familiarity with data ecosystems (e.g., SnowFlake, DataBricks), and modern ML tooling
- Strong communication, stakeholder management, and team-building skills
- Experience navigating privacy, compliance, and governance in machine learning workflows
- Preferred: Master’s degree or PhD in Computer Science, Engineering, Mathematics, or a related field