Senior Machine Learning Engineer

2 weeks ago


San Jose, United States Glint Tech Solutions LLC Full time

About the job Senior Machine Learning Engineer - Brand Ads Team

About Us
Our Brand Ads Team develops advanced technologies that empower businesses to unlock growth opportunities. We manage a suite of ad products, including reservation ads, auction ads, and creative content ads, all designed to boost brand visibility and help clients achieve their business objectives. Our work spans the complete ads technology stackcovering ad bidding, ranking, and forecastingto deliver high-impact solutions.

Role Overview
We are seeking experienced engineers with strong problem-solving abilities and a solid understanding of algorithms to build and maintain systems that excel in performance, scalability, and reliability. This role offers the chance to collaborate closely with global engineering and product teams in a fast-moving, high-impact environment.

Key Responsibilities

  • Develop innovative monetization products that drive user engagement and increase revenue.
  • Contribute to the development and scaling of large-scale ad systems.
  • Collaborate on ad algorithm development, leveraging machine learning to enhance ad effectiveness.
  • Apply NLP and computer vision techniques to advance content understanding and taxonomy classification.
  • Support the rapid growth of our team with high-quality, efficient code and solutions.
Qualifications
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field, with 3+ years of relevant experience.
  • Proficiency in programming, debugging, and optimizing in languages such as Go, C/C++, or Python.
  • Strong critical thinking skills and the ability to devise clear, effective solutions to complex problems.
  • Professional experience in machine learning, data mining, data analysis, or distributed systems.
  • In-depth knowledge in at least one of the following areas: brand ads, content ads, auction mechanisms, bidding strategies, ranking systems, or ad forecasting.
  • Hands-on experience with one or more of the following: machine learning, deep learning, NLP, recommendation engines, backend systems, or large-scale data platforms.
  • Strong product sense, with a track record of designing and implementing product-focused features.


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