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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.
Your 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
2+ years of experience with leading applied machine learning models with Tensorflow/Pytorch with large-scale ML systems
5+ 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 Health benefits
Retirement Savings plan with matching contributions
Workspace benefits for your home office
Personal & Professional development funds
Family Planning Support
Flexible Vacation & Reddit Global Days Off
