Sr Machine Learning Engineer-Brand Ads(San Jose/LA/Seattle)

Hireio - San Jose, CA

Full-time - Mid Level

San Jose, CA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Sr Machine Learning Engineer for Brand Ads will be responsible for developing and managing innovative monetization products that enhance engagement and revenue. This role involves working on a large-scale Ads system, utilizing machine learning to improve ads algorithms, and applying technologies related to natural language processing (NLP) and computer vision (CV) for content understanding. The position requires collaboration with global engineering and product teams in a dynamic and fast-paced environment.

Responsibilities

• Create innovative monetization products that drive engagement and revenue.
• Participate in the development of a large-scale Ads system.
• Participate in the development and iteration of Ads algorithms using Machine Learning.
• Work on NLP and CV related technology for content understanding and taxonomy.
• Contribute to the success of a rapidly growing and evolving organization with speediness and quality.

Requirements

• BS degree in Computer Science, Computer Engineering or other relevant majors, with 3+ years of related work experience.
• Excellent programming, debugging, and optimization skills in one or more general purpose programming languages including but not limited to: Go, C/C++, Python.
• Ability to think critically and to formulate solutions to problems in a clear and concise way.
• Relevant professional experience with machine learning, data mining, data analysis, distribution system.
• Good understanding in one of the following domains: brand ads, content ads, auction, bidding, ranking, and ads forecasting.
• Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems, backend, large-scale systems, data science, full-stack.
• Good product sense and experience designing and implementing product features.