Senior ML Engineer – Remote Real-Time Bidding & AI

Unity Enterprise; Mountain View (CA); Hybrid; USD 149,000 - 245,000; Full time

Benefits offered by this job

Health insurance

Employee stock ownership

Generous vacation and personal days

Commute subsidy

Job summary

Unity Technologies is hiring a Senior Machine Learning Engineer for the Vector Bidding Science team. You will define the technical vision and architect scalable real-time bidding systems powered by AI, marketplace intelligence, and advanced optimization frameworks.

You will develop state-of-the-art bidding and pacing algorithms, leverage large datasets, and drive offline and online experiments to maximize advertisers’ returns with cross-functional collaboration across product and engineering

Qualifications

• Hands-on experience with state-of-the-art ML, reinforcement learning, and control theory applied to real-world bidding/pricing problems.
• Strong software engineering skills in Python and experience with deep learning frameworks, preferably PyTorch.
• Solid understanding of metric design, online experimentation (A/B testing), and large-scale data analysis.

Responsibilities

• Design, implement, and optimize core bidding algorithms and auction mechanisms.
• Architect and scale bid landscape forecasting capabilities.
• Analyze large-scale marketplace dynamics to uncover insights and deliver algorithmic improvements.
• Drive offline evaluations and online A/B experiments to validate model performance and impact.
• Collaborate with product, infrastructure, and engineering teams.

Skills

Python

Reinforcement learning

Machine learning

Online experimentation

Tools

PyTorch

Spark

Ray

BigQuery

Flink

Job description

Unity Technologies is hiring a Senior Machine Learning Engineer for the Vector Bidding Science team. You will define the technical vision and architect scalable real-time bidding systems powered by AI, marketplace intelligence, and advanced optimization frameworks.

You will develop state-of-the-art bidding and pacing algorithms, leverage large datasets, and drive offline and online experiments to maximize advertisers’ returns with cross-functional collaboration across product and engineering