Ad Relevance and Ranking, Machine Learning Engineer (Staff/Senior)


March 30, 2021

San Francisco, CA, US

Imagine an on-line shopping experience where aisles or stores are dynamically constructed based on your specific requirements and preferences. Instacart Ads aims to bring such a personalized search and discovery experience to online shopping.
We are looking for an outstanding ads ranking and relevance machine learning engineer to join our team. We work on improving the relevance of ads on Instacart. Instacart ads help customers access relevant promotions/ads and help advertisers achieve their goals of reaching new customers, and retaining loyal customers. Many of these promotions help customers get prices that are lower than in-store prices and are more valuable when well-targeted. Machine Learning models play a major role in driving the selection and ranking of ads across placements and product lines, and the creation of audiences, so that we prioritize the best ad for each customer context.
  • This is a senior individual contributor role leading projects with significant impact on customer experience and revenue
  • You will build new machine learning models to improve selection and ranking of ads, or the creation of audiences based on user behavior
  • You will design and code highly scalable, machine learning applications processing large volumes of data
  • You will participate in the entire development lifecycle of ad projects - from concept to production release
  • You will collaborate with other Machine Learning Engineers, Economists, Data Scientists and Product managers in crafting and implementing your technical vision
  • You will coach and mentor the next generation of strong engineers on the team
  • Examples of current projects: Ads Targeting, Ads Quality, Ads Relevance and Ranking

  • Have experience in online advertising with a particular focus on machine learning applications for improving targeting, content relevance and ranking
  • Have strong engineering skills with expertise in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have an applied research mindset and stay close to recent developments in deep learning, unsupervised learning, recommendation systems and causal inference
  • Have experience with building large scale distributed systems
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels
  • Bonus: Familiarity with auction