Sr. Machine Learning Engineer - Search

Role overview Build and operate machine learning systems and AI features, taking work from experimentation through production deployment and monitoring. The role combines established machine learning methods, deep learning, and language model applications, with a focus on reliable systems that perform at scale.

Responsibilities - Develop, evaluate, deploy, and maintain models and AI-powered product features. - Build end-to-end pipelines for data ingestion, feature engineering, training, evaluation, and serving. - Apply language models through prompt design, retrieval-augmented generation, observability, and orchestration frameworks. - Work with backend and data engineering colleagues to integrate models into existing systems. - Monitor production performance, reliability, and fairness, and contribute to experiment tracking, versioning, CI/CD, and observability practices.

Requirements - At least three years of professional machine learning or AI engineering experience, including shipping systems to production. - Strong knowledge of supervised and unsupervised learning, feature engineering, and model evaluation. - Proficiency in Python and a deep learning framework; PyTorch is preferred. - Experience building and using APIs with a framework such as FastAPI, Flask, or Django. - Practical experience with language models, such as fine-tuning, retrieval-augmented generation, or AI applications. - Cloud and machine learning tooling experience, familiarity with Docker and software engineering practices, and advanced written and spoken English.

Nice to have - Experience with vector databases and semantic search, or a background in NLP, information retrieval, or recommendation systems. - Familiarity with model evaluation frameworks and responsible AI.