What you'll do:
- Design and implement machine learning models and algorithms to optimize ad recommendations and auction mechanisms.
- Apply advanced statistical and machine learning techniques to generate insights and improve the effectiveness of ad targeting and delivery.
- Define success metrics and develop dashboards to monitor and visualize the performance of ML models in production.
- Work closely with cross-functional teams, including Product, Engineering, and Data Science, to translate business requirements into ML solutions.
- Mentor and provide technical guidance to junior ML engineers and data scientists.
- Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques.
What you'll need:
- Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Data Science, ML, Statistics, or other quantitative fields.
- Proven experience with designing and implementing machine learning models in production environments applied to recommendation systems.
- Proficiency in using Python for developing ML models and handling large-scale data sets.
- Hands-on experience with building batch data pipelines using technologies like Spark or other map-reduce frameworks.
- 8+ years of industry experience as an ML engineer or equivalent.
- Experience with enabling production-scale and maintaining large ML models.
- Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) and one ML framework (Pytorch, Tensorflow)
- Experience with state-of-the-art deep learning techniques.
- Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines.
* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .