Machine Learning Engineer - Matching
3 Months ago • All levels • $143,100 PA - $264,200 PA
Research Development
Job Description
Apple Ads is seeking a Machine Learning Engineer to develop models that enhance their advertising platform. The role involves writing production code for recommendations, collaborating with business partners on new product development, and conducting large-scale experiments. The engineer will drive strategic outcomes through innovation in machine learning techniques and algorithms to improve the ad network. A deep understanding of ad network behavior is expected, along with the ability to prioritize an innovation roadmap. Responsibilities include leading the development and delivery of state-of-the-art capabilities. The ideal candidate will have experience developing and implementing machine learning algorithms, ideally in the ads space, with a strong understanding of scalable architectures and Agile environments. Teamwork and ability to meet tight deadlines are crucial.
Good To Have:
- Experience in the ads space
- Deep understanding of ad network behavior
Must Have:
- Develop models to improve advertising platform
- Write production code for recommendations
- Work with business partners on new products
- Perform large scale experiments
- Develop and implement ML algorithms
- Understand scalable architectures
- Work in Agile environments
- Be a good team player
At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! You'll have the opportunity to develop models that improve our platform across the board, write production code to generate recommendations, 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'll drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network. You've, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You'll lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning algorithms, ideally within the ads space. You'll have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a good team player under tight deadline constraints is key to success.
Matching at Ads is a critical component of our Ads funnel and responsible for ensuring that we are retrieving relevant and engaging Ads for our users. We are building the next generation of our retrieval systems to sustain the growth of the business for the future. We are looking for a Machine Learning Engineer that will develop the algorithms for our retrieval system. In this role you will drive step-change improvements in our outcomes, impact our platform revenue and quality of our ads, and formulate approaches to greenfield product opportunities. You will own end-to-end the ideation, development, testing and productionization of these algorithms. You will work with complex problems in the ads retrieval space, provide solution that adhere to Apple’s privacy principles, review and contribute to state of the art research, work with a variety of cross functional teams to ensure the feasibility and robustness of delivering new capabilities. This role will work closely with organizational partners and be expected to present findings across the organization.
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