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