Senior Machine Learning Engineer, Ads Demand Optimization
Salário Estimado
US$ 15.3k/mês
≈ R$ 84.332,00 - R$ 9.510,00
Regular
Score da Vaga
Descrição da Vaga
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
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:
Additional information • Relocation support is not available for this position Life at Unity We offer a wide range of benefits designed to support employees' well-being and work-life balance.
You can read more about them on our career page.
Unity [NYSE: U] is the leading platform to create and grow games and interactive experiences.
Creators, ranging from game developers to artists, architects, automotive designers, infrastructure experts, filmmakers, and more, use Unity to bring their imaginations to life across multiple platforms, from mobile, PC, and console, to spatial computing.
As of the third quarter of 2024, more than 70% of the top 1,000 mobile games were made with Unity, and in 2024, Made with Unity applications had an average of 3.7 billion downloads per month.
For more information, please visit Unity.
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 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.
Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers.
Unity does not accept unsolicited headhunter and agency resumes.
Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us.
Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy.
Should you have any concerns about your privacy, please contact us at [email protected]. #SEN #LI-AR1 • Note: Certain locations require a good faith disclosure of the base salary range for the role.
The actual salary for the successful candidate may differ based on location, experience, and other job-related factors.
Gross pay salary $183,700—$248,600 USD
Requisitos
- 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
- 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
Responsabilidades
- 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
- 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
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