Unity Technologies
Senior Machine Learning Engineer, Ads Demand Optimization
Unity Technologies, San Francisco, California, United States, 94199
Senior Machine Learning Engineer, Ads Demand Optimization
Location:
San Francisco, CA, USA
Department:
Engineering
Requisition ID:
JOBREQ-2515066
The opportunity At Unity, we’re committed to building a win‑it‑together culture grounded in respect and opportunity. Within our fast‑paced and collaborative environment, we’re tackling complex challenges that drive meaningful impact for gamers and game developers across our ecosystem. The Unity Ads Demand Optimization team plays a critical role in this effort. We build systems and algorithms for auction and bidding to optimize on behalf of advertisers, with consideration of multiple factors (e.g. objective, budget, target ROAS and so on). We design optimized solutions for campaign products to improve advertisers' experience.
We are seeking skilled MLEs to design and implement AI‑native demand optimization algorithms and systems. You will own end‑to‑end solutions that power autobidding, auction mechanics, and reinforcement learning strategies for ads and games. This role is highly cross‑functional and impact‑driven, working closely with product, engineering, and scientists to deliver measurable improvements in delivery efficiency, revenue, and user experience.
What you'll be doing
Architect and implement automated bidding strategies to improve delivery efficiency
Design, prototype, and productionize new bidding algorithms and products, including model training, policy evaluation, and guardrail enforcement.
Develop and refine auction mechanisms that balance multiple objectives under constraints.
Build exploration frameworks and reinforcement learning strategies for cold‑start scenarios (new ads/new games), including contextual bandits, off‑policy evaluation, and online learning.
Own the full lifecycle: problem framing, data instrumentation, modeling, simulation, experimentation, and deployment with continuous monitoring and iteration.
What we're looking for
Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, or a related field—or equivalent practical experience.
Strong foundation in: reinforcement learning, contextual bandits, and exploration‑exploitation strategies; auction theory, mechanism design, and multi‑objective optimization; probabilistic modeling, causal inference, and counterfactual evaluation; online learning, off‑policy evaluation, simulation, and A/B testing.
Proficiency with Python and common ML libraries (e.g., PyTorch, TensorFlow, JAX); experience with data processing (e.g., Spark, SQL) and experiment platforms.
Demonstrated ability to translate business objectives into robust algorithmic solutions and measurable outcomes.
3+ years of hands‑on experience building and operating large‑scale Ads delivery and optimization systems.
Additional information
Relocation support is not available for this position.
Salary $183,700—$248,600 USD
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form (https://docs.google.com/forms/d/e/1FAIpQLSdrbRLG1N-apH1eahQ622Gypo-rmiAB6LLTP1UsSWQNu7omxQ/viewform) to let us know.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
#J-18808-Ljbffr
San Francisco, CA, USA
Department:
Engineering
Requisition ID:
JOBREQ-2515066
The opportunity At Unity, we’re committed to building a win‑it‑together culture grounded in respect and opportunity. Within our fast‑paced and collaborative environment, we’re tackling complex challenges that drive meaningful impact for gamers and game developers across our ecosystem. The Unity Ads Demand Optimization team plays a critical role in this effort. We build systems and algorithms for auction and bidding to optimize on behalf of advertisers, with consideration of multiple factors (e.g. objective, budget, target ROAS and so on). We design optimized solutions for campaign products to improve advertisers' experience.
We are seeking skilled MLEs to design and implement AI‑native demand optimization algorithms and systems. You will own end‑to‑end solutions that power autobidding, auction mechanics, and reinforcement learning strategies for ads and games. This role is highly cross‑functional and impact‑driven, working closely with product, engineering, and scientists to deliver measurable improvements in delivery efficiency, revenue, and user experience.
What you'll be doing
Architect and implement automated bidding strategies to improve delivery efficiency
Design, prototype, and productionize new bidding algorithms and products, including model training, policy evaluation, and guardrail enforcement.
Develop and refine auction mechanisms that balance multiple objectives under constraints.
Build exploration frameworks and reinforcement learning strategies for cold‑start scenarios (new ads/new games), including contextual bandits, off‑policy evaluation, and online learning.
Own the full lifecycle: problem framing, data instrumentation, modeling, simulation, experimentation, and deployment with continuous monitoring and iteration.
What we're looking for
Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, or a related field—or equivalent practical experience.
Strong foundation in: reinforcement learning, contextual bandits, and exploration‑exploitation strategies; auction theory, mechanism design, and multi‑objective optimization; probabilistic modeling, causal inference, and counterfactual evaluation; online learning, off‑policy evaluation, simulation, and A/B testing.
Proficiency with Python and common ML libraries (e.g., PyTorch, TensorFlow, JAX); experience with data processing (e.g., Spark, SQL) and experiment platforms.
Demonstrated ability to translate business objectives into robust algorithmic solutions and measurable outcomes.
3+ years of hands‑on experience building and operating large‑scale Ads delivery and optimization systems.
Additional information
Relocation support is not available for this position.
Salary $183,700—$248,600 USD
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form (https://docs.google.com/forms/d/e/1FAIpQLSdrbRLG1N-apH1eahQ622Gypo-rmiAB6LLTP1UsSWQNu7omxQ/viewform) to let us know.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
#J-18808-Ljbffr