Reddit has a flexible first workforce! if you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the United States or Canada.Ads Targeting ML engineers are focused on designing and implementing ML systems and solutions for improving targeting products. The team's projects involve building large-scale offline & online retrieval systems across several dimensions to improve contextual & behavioral targeting for targeting products.As a staff machine learning engineer in the ads targeting quality team, you will own and execute our mission to automate targeting and deliver the most relevant audiences to advertisers under the right context with ML-driven solutions. Your Responsibilities:Own end-to-end design and execution of ML-based targeting products like auto targeting, user lookalikes etc. Drive research direction and technical roadmap for complex projects, lead day to day project execution, and contribute meaningfully to team vision and strategyBe a thought leader for the team and collaborate closely with product managers and cross-functional partners to develop and prioritize the roadmap based on data analysis, industry research and product research Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two tower models, LLMs) with a focus on improving advertiser outcomesProvide mentorship to junior MLEsOwn offline & online experimentation of ML models for improving targeting products Work on large scale data systems, and product integrationCollaborate closely with multiple stakeholders cross product, engineering, research and marketing Required QualificationsTech lead experience in a product ML team driving the research and technical direction to improve business outcomes using applied MLExperience with ads retrieval modeling, ranking or recommendation systems Experience with deep learning models for retrieval (two tower, GNNs, transformers, LLMs)5+ years of end-to-end experience of training, evaluating, testing, and deploying machine learning models2+ years of experience building machine learning models with Tensorflow/Pytorch Experience with large scale data processing & pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQueryExperience working with nearest-neighbor search systems is a big plusExperience working with cross functional stakeholders across research, product & infrastructure to productize ML research Experience with deep learning, representation learning or transfer learning is preferredTech lead experience in a product team is strongly preferredBenefits:Comprehensive Healthcare Benefits401k MatchingWorkspace benefits for your home officePersonal & Professional development fundsFamily Planning SupportFlexible Vacation (please use them!) & Reddit Global Wellness Days4+ months paid Parental LeavePaid Volunteer time off
