Director of ML — Lead Scalable Personalization & Value

Unity; Mountain View (CA); On-site; USD 250,000 - 325,000; Full time

Benefits offered by this job

Employee stock ownership

Commuter subsidy

Competitive retirement plans

Generous vacation and personal days

Family-care support

Job summary

Unity is seeking a visionary Director of Machine Learning to lead the User Value team in Mountain View, guiding ML initiatives that translate into advertiser value.

You will manage a high-performing organization of scientists and ML engineers, shaping a 1–3 year technical roadmap and collaborating with Product, Design, and Data Science to identify opportunities where ML adds measurable value.

Qualifications

• 8+ years of experience in machine learning and software engineering.
• 4+ years of experience managing teams of scientists and ML engineers.
• Experience shipping ML systems at scale in personalization, recommendations, information retrieval, or behavioral modeling.
• Strong ability to articulate complex technical concepts to non-technical executives and cross-functional partners.
• MS or PhD in CS/ML/Statistics or equivalent practical experience.

Responsibilities

• Shape the ML Vision: define 1-3 year technical roadmap for user value modeling aligned with product goals.
• Lead and scale teams: mentor, recruit, and retain applied scientists and ML engineers.
• Drive product impact: partner with Product, Design, and Data Science to unlock value with ML.
• Advance the technical stack: oversee scalable ML systems including personalization, recommendations, multi-task learning, RL, and LLM integration.
• Balance innovation and execution: establish frameworks for A/B testing and guardrails to improve customer trust.

Education

MS or PhD in Computer Science / Machine Learning / Statistics

Job description

Unity is seeking a visionary Director of Machine Learning to lead the User Value team in Mountain View, guiding ML initiatives that translate into advertiser value.

You will manage a high-performing organization of scientists and ML engineers, shaping a 1–3 year technical roadmap and collaborating with Product, Design, and Data Science to identify opportunities where ML adds measurable value.