Senior Machine Learning Engineer, Ads Modeling

Unity Vector’s Ads Modeling team is seeking a Senior Machine Learning Engineer to advance ads recommendation algorithms that support more personalized ads experiences. The role combines ads business understanding, foundational model research, fast validation using large-scale compute, and production-focused collaboration with engineering and product teams.

Role Focus

You will contribute to the research and delivery of models for ads recommendations, with emphasis on understanding how ads products operate and how user interaction data can be used effectively. Work spans from defining modeling directions to validating approaches quickly and translating research into production.

Responsibilities

• Develop a strong understanding of the ads business, including the product offering, advertiser goals, the ads serving funnel, and rich real-time and dynamic user interaction data.
• Lead foundational research for new models and paradigms.
• Use rich user data and large-scale compute to validate models rapidly.
• Work closely with engineering and product teams to productionalize research.

Requirements

• Hands-on experience applying state-of-the-art machine learning and deep learning methods to complex real-world problems, specifically in user behavior modeling.
• Proficiency in Python and PyTorch, including experience with deep learning frameworks.
• Solid understanding of metric design, large-scale data analysis, and distributed computing frameworks.
• Demonstrated ability to drive projects end-to-end, address critical cross-team problems, and deliver measurable business results.

Technologies

• Python
• PyTorch

Compensation and Location

Location: Mountain View, CA (onsite)

Gross Annual Base Salary Range (anticipated):

• Zone A: USD 188,200 - 244,600
• Zone B: USD 167,200 - 217,300
• Zone C: USD 148,700 - 193,300

Beyond base salary, the role may be eligible for equity awards and participation in company incentive plans, such as annual discretionary bonuses or sales commissions. The final offer will depend on geographic location and the candidate’s relevant experience, professional background, and skill set.

Benefits

• Comprehensive health, life, and disability insurance
• Commute subsidy
• Employee stock ownership
• Competitive retirement/pension plans
• Generous vacation and personal days
• Support for new parents through leave and family-care programs
• Office food snacks
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program