Senior Search Engineer - Services Special Projects
Core
Design, build, and optimize large-scale, real-time search systems at the intersection of Generative AI and Information Retrieval, merging traditional keyword search with vector-based semantic search to personalize user experiences.
Role type
Senior IC Search Systems Engineer (Generative AI & Information Retrieval)
Builds
Large-scale, low-latency search infrastructure and intelligent ranking systems
Domain
Generative AI, Information Retrieval, Search Infrastructure
Deliverable
production ML models
Required skills
Large-scale search system design, Multi-stage ranking algorithms, NLP pipelines (intent classification, entity extraction), Vector search (embedding models, vector databases), Deep learning architectures (transformers, cross-encoders, GNNs), Real-time system optimization, Model retraining pipelines, Go, Java, C++, Python, PyTorch, XGBoost, Cloud environments (AWS), Containerization (Docker, Kubernetes), Data processing (Spark, Flink), LLM deployment and optimization, Model tuning (quantization)
Preferred skills
Graph databases (TigerGraph), Data/model versioning (DVC, MLflow, Weights & Biases), KV Stores (SSTables, Cassandra), Inference runtimes/compilers (ONNX Runtime, TensorRT, vLLM, SGLang, Triton, TorchServe)
Technologies
PyTorch, XGBoost, Spark, Flink, FAISS, Apache Kafka, OpenSearch, Elasticsearch, AWS, Docker, Kubernetes, TigerGraph, DVC, MLflow, Weights & Biases, ONNX Runtime, TensorRT, vLLM, SGLang, Triton, TorchServe
Responsibilities
Design and implement machine learning models (Learning to Rank, Cross Encoder) and multi-stage reranking algorithms, Develop and optimize ranking, relevance, and retrieval through ML/AI models, Build offline and online evaluation metrics and A/B testing frameworks, Partner with Research Scientists, Product, Data Engineering, MLOps, Search Infrastructure teams, and UX, Stay current with latest research in search and information retrieval
Seniority
Senior, hands-on IC
