About the Role
- - - - What the Candidate Will 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.
- Monitor and ensure the reliability of ML Predictions at large scale.
- Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques.
- - - - Basic Qualifications ----
- 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.
- - - Preferred Qualifications ----
- 2 years of industry experience as an ML engineer or equivalent.
- Experience with enabling production-scale and debugging large ML models.
- Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
- Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines.
For New York, NY-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.