Principal ML Engineer: Ads Personalization & Modeling

LE130 Unity Technologies SF; Mountain View (CA); On-site; USD 197,000 - 325,000; Full time

Benefits offered by this job

Health insurance

Employee stock ownership

Competitive retirement plans

Generous vacation days

Job summary

Unity Technologies SF is seeking a Principal Machine Learning Engineer to join the Vector Ads Modeling team. You will work with a high-performing team to advance ads recommendation algorithms and deliver personalized ads experiences at scale.

You will design modeling roadmaps, perform foundational research, and collaborate with engineering to productionalize research while leveraging large-scale data and compute to validate models and drive measurable business impact.

Qualifications

• Hands-on experience applying state-of-the-art ML and DL to real-world problems, especially user behavior modeling.
• Proficiency in Python, PyTorch and deep learning frameworks.
• Solid understanding of metric design, large-scale data analysis, and distributed computing.
• Proven ability to drive projects end-to-end with measurable business results.

Responsibilities

• Identity opportunities and design modeling roadmap that addresses customer needs.
• Drive foundational research for new models and paradigms.
• Leverage rich user data and large-scale compute to validate models rapidly.
• Collaborate closely with engineering and product teams to productionalize research.

Skills

Python

PyTorch

Deep learning

Machine learning

User behavior modeling

Distributed computing

Metric design

Large-scale data analysis

Strategic impact

Tools

Python tools

PyTorch

Job description

Unity Technologies SF is seeking a Principal Machine Learning Engineer to join the Vector Ads Modeling team. You will work with a high-performing team to advance ads recommendation algorithms and deliver personalized ads experiences at scale.

You will design modeling roadmaps, perform foundational research, and collaborate with engineering to productionalize research while leveraging large-scale data and compute to validate models and drive measurable business impact.