Member of Technical Staff, Machine Learning

Role overview Develop and operate machine learning models that help a consumer communication product retrieve relevant context, rank results, and adapt to user behavior. The work spans model development, evaluation, deployment, and production improvement, with attention to both quality and operational cost.

Responsibilities - Build and improve models for classification, retrieval, ranking, recommendations, and personalization. - Improve search and context retrieval using embeddings, vector search, hybrid methods, and reranking. - Create evaluation datasets, pipelines, and metrics to measure model quality and detect regressions. - Train, fine-tune, deploy, and monitor models through production ML workflows. - Investigate production issues and use evaluation findings and user feedback to guide improvements. - Balance accuracy and precision with latency, compute cost, and reliability.

Requirements - At least 3 years of machine learning engineering experience, including production deployments. - Strong Python skills and practical experience with PyTorch or JAX. - Solid grounding in machine learning algorithms, training, and evaluation. - Experience with classification, ranking, retrieval, recommendation, or personalization models. - Familiarity with embeddings, vector search, or information retrieval systems. - Experience building data pipelines, training workflows, and inference services. - Ability to assess model quality with relevant metrics and experiments.

Nice to have - Experience with transformer models, language model fine-tuning, or embedding models. - Background in hybrid search, reranking, or retrieval evaluation. - Consumer recommendation or personalization experience, or work on large-scale training and inference infrastructure.