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Senior Machine Learning Engineer, Ads Targeting
2 weeks ago
Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With ,+ active communities and approximately M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit . 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. We’re evolving and continuing our mission to bring community, belonging, and empowerment to everyone in the world. Providing a delightful and relevant experience to our users applies to our Ads like all of our offerings, and we’re excited to build a product that is best-in-class for our users and advertisers. The year ahead is a busy one - join us 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 senior machine learning engineer in the ads targeting core team, you will execute our mission to automate targeting and deliver the most relevant audiences to advertisers under the right context with data and ML-driven solutions. Responsibilities: Own end-to-end execution of ML-based targeting products like smart targeting expansion, keyword targeting, auto targeting, user lookalikes etc Own offline & online experimentation of ML models for improving targeting products to drive advertiser outcomes Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two tower models) with a focus on improving advertiser outcomes Drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy Work on large scale data systems, backend services and product integration Collaborate closely with multiple stakeholders cross product, engineering, research and marketing Required Qualifications: + years of experience with leading applied machine learning models with Tensorflow/Pytorch with large-scale ML systems + years of end-to-end experience of training, evaluating, testing, and deploying machine learning models Experience with large scale data processing & pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQuery Experience working with nearest-neighbor search systems is a big plus Experience building & improving MLOps tools and ML experimentation workflows Experience working with cross functional stakeholders across research, product & infrastructure to productize ML research Knowledge of large scale search & recommender systems, or modern ads ranking/retrieval/targeting systems is preferred Experience with deep learning, representation learning or transfer learning is preferred Tech lead experience in a product team is strongly preferred Benefits: Comprehensive Healthcare Benefits k Matching Workspace benefits for your home office Personal & Professional development funds Family Planning Support Flexible Vacation (please use them) & Reddit Global Wellness Days + months paid Parental Leave Paid Volunteer time off LI-Remote LI-CJ Pay Transparency: This job posting may span more than one career level. To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base pay range for this position is:$,—$, USD
