Machine Learning Engineer
Python
Artificial Intelligence
Data Analysis
Data Engineer
Data Pipeline
Data Processing
Data Science
Database
Databases
DevOps
Engineer
Information Technology (IT)
Machine Learning
Machine Learning Deployment
Machine Learning Engineer
Machine Learning Pipelines
Ml Ops
Programming
Programming Language
Programming Languages
Software Development
Job Description
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 productionize new algorithms
Required Qualifications
- 4+ years of machine learning engineering experience
- Strong proficiency in Python and ML frameworks, including PyTorch and TensorFlow
- 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
- PyTorch
- TensorFlow
- 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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