Machine Learning Engineer
Core
Design, implement, and deploy ML models for memory retrieval, ranking, and contextual understanding to power intelligent memory systems.
Role type
Senior Machine Learning Engineer (Retrieval & Infrastructure)
Builds
Scalable ML infrastructure, production ML models, and training pipelines for memory systems
Domain
AI/ML, Information Retrieval, NLP
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, MLOps, model serving, monitoring, NLP, embeddings, retrieval systems, cloud platforms (AWS/GCP), containers, large-scale data processing
Preferred skills
Large language models, prompt engineering, vector databases (Pinecone, Weaviate, Milvus), recommendation systems, search, model optimization, quantization, real-time ML systems, transformer architectures
Technologies
PyTorch, TensorFlow, AWS, GCP, Pinecone, Weaviate, Milvus
Responsibilities
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
Seniority
Senior, hands-on IC
