Manager 3, AI Science (MLOps, AI, Data Science)

Location: Mountain View, California, or San Diego, California

Salary: $264,500–$357,500 base pay annually in Mountain View

Company

hirify.global is a global financial technology platform operating products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Lead a multi-team AI Science organization across MarTech, data, and third-party data acquisition.
• Shape technical strategy for AI-ready architectures, semantic layers, knowledge infrastructure, and production ML systems.
• Design verification, evaluation, and feedback layers for entity resolution, business metrics, semantic outputs, and agentic AI workflows.
• Guide digital-twin models for marketing and sales, including audience segments, product lineups, pricing, and scenario simulation.
• Drive anomaly detection for data quality, pipeline lineage, distribution shifts, and semantic drift.
• Partner with Product, Design, Engineering, Customer Success, HR, and senior technical leaders to scale AI-native solutions and teams.

Requirements

• 10+ years of experience in AI/ML, Data Science, or MLOps, with technical depth in algorithmic modeling, production ML systems, or applied data science.
• 3+ years of people management experience, including management of principal or senior/staff-level individual contributors across multiple teams.
• Experience shaping technical strategy and architecture for AI/ML systems at scale, from data curation through production deployment.
• Strong hands-on experience with MLOps, production-grade models, data pipelines, AI engineering standards, semantic layers, knowledge graphs, entity resolution, and anomaly detection.
• Strong proficiency in Python and ML frameworks, with working knowledge of AWS, GCP, or Databricks ML infrastructure.
• Bachelor’s degree in Computer Science, Statistics, Data Science, or a related quantitative field; a Master’s degree or PhD is preferred.

Nice to have

• Experience with generative AI, LLM systems, agentic AI architectures, evaluation design, reinforcement learning, fine-tuning, or prompt optimization.
• Experience building digital twins, simulation models, continuously updating data systems, or third-party data integrations.
• Experience scaling AI Science or Data Science teams and driving adoption of shared platforms in a large technology organization.

Culture & Benefits

• Competitive compensation with pay-for-performance rewards.
• Potential eligibility for cash bonus, equity rewards, and employee benefits.
• Work across a complex, cross-functional technology organization focused on AI-native development and governed data.
• Focus on leadership development, mentorship, succession planning, and technical growth.