Unity Technologies

Game Engine

SeniorMachineLearningEngineer,VectorBiddingScience

$149–259k Mountain View, California, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning Engineer, Vector Bidding Science at Unity Technologies. Skills: Machine Learning, Python, Real-time Bidding, AI. Design bidding algorithms. Implement bidding algorithms”

What You'll Achieve.

automatically maximize advertisers’ returns; deliver measurable business impact

Industry & Context.

Game Engine
Problems you'll solve

advanced optimization frameworks; uncover deep insights; deliver algorithmic improvements; validate model performance; deliver measurable business impact; ambiguous technical landscape

Eligibility Requirements

Relocation support is not available

What They're Looking For.

Must Have

state-of-the-art machine learning, reinforcement learning, control theory, complex, real-world bidding or pricing problems, software engineering skills in Python, deep learning frameworks, metric design, online experimentation frameworks (A testing), large-scale data analysis, lead projects end-to-end, deliver measurable business impact, ambiguous technical landscape

Nice to Have

large datasets, distributed computing frameworks, Spark, Ray, BigQuery, Flink, real-time ad systems, DSP (Demand-Side Platform) bidding logic, survival analysis for market price estimation, game-theoretic modeling, AI tools, Claude Code, GitHub Copilot, Cursor

What You'll Do.

Design bidding algorithms

Implement bidding algorithms

Optimize bidding algorithms

Architect bid forecasting

Scale bid forecasting

Analyze marketplace dynamics

Deliver algorithmic improvements

Drive offline evaluations

Drive online A experiments

Validate model performance

Deliver business impact

How You'll Work.

Team & Collaboration

Collaborate cross-functionally with product; Collaborate cross-functionally with infrastructure; Collaborate cross-functionally with engineering teams

Communication Scope

professional verbal and written exchanges in English

Process & Methodology

lead projects end-to-end

Full Job Description

The opportunity We are looking for Senior Machine Learning Engineers to join our Vector Bidding Science team. In this role, you will define the technical vision and architect the next generation of scalable real-time bidding systems powered by cutting-edge AI, marketplace intelligence, and advanced optimization frameworks. As a key member of the Vector AI org, you will play a pivotal role in advancing Unity’s high-scale ads engine. By harnessing massive datasets and rich signals, you will develop state-of-the-art bidding and pacing algorithms that automatically maximize advertisers’ returns. What you'll be doing Design, implement, and optimize core bidding algorithms and auction mechanisms Architect and scale bid landscape forecasting capabilities Analyze large-scale marketplace dynamics to uncover deep insights and deliver algorithmic improvements Drive offline evaluations and online A/B experiments to validate model performance and deliver measurable business impact Collaborate cross-functionally with product, infrastructure, and engineering teams What we're looking for Hands-on experience on state-of-the-art machine learning, reinforcement learning, and control theory to complex, real-world bidding or pricing problems Strong software engineering skills in Python and experience with deep learning frameworks, preferably PyTorch Solid understanding of metric design, online experimentation frameworks (A/B testing), and large-scale data analysis Proven ability to lead projects end-to-end and deliver measurable business impact in an ambiguous technical landscape You might also have Experience working with large datasets and distributed computing frameworks (e.g., Spark, Ray, BigQuery, Flink) Experience building real-time ad systems, specifically in DSP (Demand-Side Platform) bidding logic, survival analysis for market price estimation, or game-theoretic modeling Experience leveraging AI tools (such as Claude Code, GitHub Copilot, and Cursor) to accelerate development A

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