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Machine Learning Engineer

Engramme San Francisco, California, United States

2 d ago
machine-learning Mid (2-5 yrs) Full-time United States
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About the role

Design and implement machine learning models for memory retrieval and ranking while building scalable infrastructure and training pipelines. You will also deploy and monitor models in production, optimize performance for real-time systems, and collaborate with the research team.

What they look for

Python PyTorch TensorFlow Machine Learning MLOps NLP Embeddings Retrieval Systems AWS GCP Containers Large Language Models Prompt Engineering Vector Databases Recommendation Systems Transformer Architectures

Requirements

Requires 4+ years of machine learning engineering experience with strong proficiency in Python and frameworks like PyTorch or TensorFlow. Candidates must have experience deploying models to production, knowledge of MLOps, and a solid understanding of NLP and retrieval systems.

Full description

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

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