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Machine Learning Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Engramme
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 140000 - 200000 USD Yearly USD 140000.00 200000.00 YEAR
Job Description & How to Apply Below

Engramme is seeking a Machine Learning Engineer in San Francisco, CA to build and deploy machine learning systems focused on memory retrieval and contextual understanding. The role emphasizes scalable ML infrastructure, production deployment, and real-time performance optimization.

What You Will 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
  • Apply MLOps best practices
    , including monitoring and operational readiness
  • Collaborate with the research team to product ionize new algorithms
Required Qualifications
  • 4+ years of machine learning engineering experience
  • Strong proficiency in Python and ML frameworks, including Py Torch and Tensor Flow
  • Experience deploying ML models into production environments
  • Knowledge of MLOps
    , model serving
    , and monitoring
  • Understanding of NLP
    , embeddings
    , and retrieval systems
  • Experience with cloud platforms such as AWS and GCP
    , and containers
  • Strong software engineering fundamentals
  • Experience with large-scale data processing
Technologies You Will Work With
  • Python
  • Py Torch
  • Tensor Flow
  • AWS
  • GCP
  • Containers
  • Vector databases and embedding systems
Nice to Have
  • Experience with large language models and prompt engineering
  • Knowledge of vector databases including Pinecone
    , Weaviate
    , or 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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