Build and deploy ML models for memory retrieval and contextual understanding. Create scalable ML infrastructure that powers intelligent memory systems. WHAT YOU'LL DO - Design and implement ML models for memory retrieval and ranking - Build ML infrastructure and training pipelines - Deploy and monitor models in production at scale - Optimize model performance and latency for real-time systems - Work with vector databases and embedding systems - Implement MLOps best practices and monitoring - Collaborate with research team to productionize new algorithms WHAT WE'RE LOOKING FOR - 4+ years of ML engineering experience - Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow) - Experience deploying ML models to production - Knowledge of MLOps, model serving, and monitoring - Understanding of NLP, embeddings, and retrieval systems - Experience with cloud platforms (AWS, GCP) and containers - Strong software engineering fundamentals - Experience with large-scale data processing NICE TO HAVE - Experience with large language models and prompt engineering - Knowledge of vector databases (Pinecone, Weaviate, Milvus) - Experience with recommendation systems or search - Background in information retrieval or ranking systems - Knowledge of model optimization and quantization - Experience with real-time ML systems - Familiarity with transformer architectures