New York City, NY30+ days ago
THE STATSWhat were looking for in our next teammate3-5+ Years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)Experience implementing vector search, semantic search, or embedding-based retrieval systems for production ML or AI applicationsExperience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflowsExperience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalization models) to improve relevanceHands-on experience in deploying ML and GenAI/LLM models under the constraints of scalability, correctness, and maintainability. Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face Transformers, etc).Hands on experience with one or more ML and GenAI/LLM cloud services (Amazon SageMaker, Amazon Bedrock, Databricks Mosaic AI, Seldon, Arize, etc)Experience contributing to various software architecture design, with some emphasis on scalable architectures supporting both traditional ML and advanced LLM workflows.