Pinterest is looking to evolve the machine learning technology stack within Ads Ranking to advance statistical models that power ads engagement and delivery, connecting Pinners with partner products.
Requirements
Experience with large scale data processing (e.g. Hive, Scalding, Spark, Hadoop, Map-reduce).
Experience in working in frontend, backend and ML systems for large-scale user-facing products, and have a good understanding of how they all work.
Strong software engineering and mathematical skills with knowledge of statistical methods.
Hands-on experience with large-scale online e-commerce systems is a plus.
Background in computational advertising is preferred.
Responsibilities
Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML.
Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery.
Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost.
Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements.
Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals.
Other
12+ years of industry experience in the engineering teams that build large-scale ML-driven user-facing products.
6+ years of technical leadership experience; leading cross-team engineering efforts that improves user experience in products.
Strong execution skills in project management.
Masters or PhD in computer science, machine learning, statistics, or related fields, or equivalent experience.
Experience in closely collaborating with product managers/designers to ship ML-driven user-facing product.
This position is not eligible for relocation assistance.
This role will need to be in the office for in-person collaboration 1-2 times/month and therefore can be situated anywhere in the country.
