Search Engineer Services Special Projects

Our team is building a massive real-time search experience from the ground up one that will reach users at Apple scale. Its search at the intersection of Generative AI and Information Retrieval and its a rare opportunity to shape a product that millions will rely are seeking a highly experienced and innovative Search Systems Engineer to help design develop and optimize large-scale search systems. n

This role is ideal for a technically deep individual who has a strong product sense and enjoys solving real-world problems using modern AI models and scalable systems. We are a passionate team of hardworking engineers and scientists and we are looking for a strong Search engineer to join us. You will work closely with AI/ML Scientists and engineers at the intersection of Generative AI and Information Retrieval crafting intelligent systems that personalize user experiences.n

Search Architecture: Design build and maintain large-scale low-latency high-performance search systems that can and optimize search and retrieval systems: Develop and optimize ranking relevance and retrieval through ML/AI models and merging traditional keyword search with vector-based semantic search using embedding models and vector Understanding: Develop sophisticated NLP pipelines for intent classification entity extraction semantic parsing and query u0026 Ranking: Design and Implement machine learning models (e.g. Learning to Rank Cross Encoder based models) and multi-stage reranking algorithms to optimize search precision and u0026 Tuning: Build offline and online evaluation metrics A/B testing frameworks and continuous improvement strategies for search quality nCollaborate cross-functionally: Partner with Research Scientists Product Data Engineering MLOps Search Infrastructure teams and UX to align search features with business and user search research: Stay current with the latest research and innovations in search and information retrieval technologies translating them into scalable production systems.

Bachelors degree in Computer Science Machine Learning Statistics or a related fieldn8 years of experience in Machine Learning Data Science or Software Engineering roles with a significant focus on search infrastructure and information experience building and deploying large-scale search systems in proficiency in C Go Python or JavanDeep familiarity with ML frameworks (TensorFlow PyTorch XGBoost etc.).nSolid understanding of ML system design model lifecycle and experimentation experience working with large datasets data processing pipelines (e.g. Spark Flink) and scalable understanding of information retrieval ranking algorithms and user modeling with real-time systems user feedback loops and model retraining Infrastructure: Hands-on experience with vector databases such as Milvus Qdrant Pinecone or knowledge of cloud environments (AWS or GCP) and containerization (Docker Kubernetes)nExperience building streaming platforms such as Apache Kafka or comparable message brokersnExperience with search infrastructure such as OpenSearch Elasticsearch or similar search-based stacksnExcellent communication skills and a collaborative mindsetn

Masters Degree; PhD Preferred nPublished work or patents in the domain of search systems information retrieval or related ML foundation in deep learning architectures for search and retrieval (e.g. transformers graph neural networks learned sparse representations).nExposure to multi-objective optimization in search systems (e.g. relevance diversity freshness fairness).nFamiliarity with MLOps tools and cloud platforms (AWS/GCP MLflow etc.)nExperience with graph databases such as TigerGraphnExperience with data and model versioning tools and practices (e.g. DVC MLflow Weights u0026 Biases)n