Machine Learning Scientist - Ad Campaign Optimization
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Job Location:
Cupertino, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Were seeking a self-motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace. You will develop models and systems that improve our platform across the board develop production code to generate high quality ad recommendations and work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You will also drive strategic outcomes through meaningful innovation in multiple fields by owning the development and application of sophisticated techniques and algorithms to improve our ad network. You have or will develop a deep understanding of the ad network behavior and will partner with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You will lead the conception development and delivery of innovative capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning or optimization algorithms ideally within the ads space recommendations or search relevance. You will have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a great teammate under potentially tight constraints is key to success.
- 3 years of experience building machine learning and quantitative optimization capabilities across many different product areas at scale
- Experience in machine learning quantitative methods control systems or reinforcement learning
- Ability to apply and implement research concepts ultimately in production quality code
- Experience defining clear testable research hypotheses including intended impact on the business
- Deep knowledge of design of experiments online experimentation approaches preferably at scale
- Ability to formulate and advocate for R&D objectives and results to cross-functional team members including executive business leadership and product management
- Experience contributing and/or reviewing research for top conferences and publications
- Deep fluency in Java or Python
- Experience with Spark Hadoop or other distributed frameworks
- BS or equivalent experience in Machine Learning Statistics Control Theory Forecasting Optimization Reinforcement Learning or related field with experience building production systems
- 5 years of experience building machine learning and quantitative optimization capabilities across many different product areas at scale
- MS or PhD or equivalent experience in Machine Learning Statistics Control Theory Forecasting Optimization Reinforcement Learning or related field with experience building production systems
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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