Senior Machine Learning Engineer (Ads Auction, Ads Bidding, Ads Reservation)

Company : Macpower Digital Assets Edge
Location : Seattle, WA, 98104
Posted Date : 15 September 2025
Job Details
The Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting. We are looking for seasoned engineers that have strong problem-solving skills and algorithm understanding to build and manage systems with high performance, scalability, and availability. You will have the opportunity to partner closely with a globalized engineering and product teams in a high-impact and fast-paced environment.
WHAT YOU'LL DO:
- 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 by 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.
- 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.
- bility 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.
- 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.
- Go
- C/C++
- Python
- Machine Learning
- Deep Learning
- NLP
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