Staff Machine Learning Engineer, Retrieval & Targeting

What you'll do

• Set technical direction and roadmap for ads retrieval modeling; mentor engineers and partner with cross-functional teams.
• Design, develop, evaluate, and launch retrieval and candidate-generation models, improving the retrieval stack and its production practices.
• Lead offline analysis and online experiments, connecting retrieval metrics to downstream ads and user outcomes.

What they ask for

• 7+ years of industry experience, including substantial experience building and shipping applied ML products.
• Deep experience in information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
• Experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
• Demonstrated ownership of ML projects through production launch, plus technical leadership experience.

Nice to have

• Experience in ads retrieval, ranking, targeting, ad serving, recommendation, search relevance, or marketplace optimization.
• Experience with sequential modeling (e.g., RNNs, Transformers), graph, or multimodal signals.

Pay

$230,000 — $322,000 USD (base salary)

Tools

TensorFlow, PyTorch, DNN, embeddings, two-tower, dual-encoder models, approximate nearest-neighbor search, Transformers

AI focus

Applied machine learning for ads retrieval and targeting, including candidate generation, representation learning, deep learning, and model evaluation. AI may also be used to record, transcribe, and summarize interviews in select roles and locations; candidates may opt out.