Staff Machine Learning Engineer, Ads Modeling

DataJobs; Mountain View (CA); On-site; USD 172,000 - 284,000; Full time

Benefits offered by this job

Comprehensive health, life, and dental

Commute subsidy

Employee stock ownership

Retirement plans

Generous vacation and personal days

Parental leave support

Office snacks

Mental Health resources

Employee Resource Groups

Training and development

Volunteer and donation matching

Job summary

Unity Technologies SF is seeking a Staff Machine Learning Engineer for the Vector Ads Modeling team in Mountain View, CA onsite. You will advance ads recommendation algorithms through research and productionization, partnering with engineers and product teams to bring models into production.

Responsibilities include shaping a modeling roadmap, leading foundational research, and applying large-scale data to validate models.

Qualifications

• Hands-on experience applying state-of-the-art ML and DL models to real-world problems with a focus on user behavior.
• Proficiency in Python and PyTorch, with a solid understanding of metric design and large-scale data analysis.

Responsibilities

• Identify opportunities and shape a modeling roadmap addressing customer needs.
• Lead foundational research for new models and paradigms.
• Partner with engineering and product teams to productionalize research outcomes.

Skills

Machine learning

Deep learning

Python

PyTorch

Distributed computing

Tools

Python

PyTorch

Job description

Unity Technologies SF is hiring a Staff Machine Learning Engineer for the Vector Ads Modeling team in Mountain View, CA (onsite). This role advances ads recommendation algorithms to support personalized ads experiences through research and productionalization.

Role Overview

Unity Vector is positioned as an AI-powered advertising ecosystem. In this position, you will work on the modeling and research efforts that improve how ads are recommended, translating new approaches into production systems with engineering and product partners.

Key Responsibilities

• Identify opportunities and shape a modeling roadmap that addresses customer needs.
• Lead foundational research efforts for new models and paradigms.
• Use rich user data and large-scale compute to validate models quickly.
• Partner closely with engineering and product teams to productionalize research outcomes.

Required Qualifications

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

Technologies

• Python
• PyTorch

Compensation and Additional Details

Salary Range: USD 172,200 - 283,900 per year.

• Zone A: $218,400 - $283,900 USD
• Zone B: $194,100 - $252,300 USD
• Zone C: $172,200 - $223,900 USD

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 depends 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

About Unity

Unity (NYSE: U) powers play for more 3 billion consumers each month through the world’s leading game engine. Unity also enables teams across industries such as automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D.