Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Machine Learning Engineer role.

Rezi rewrites your resume against Engramme's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Machine Learning Engineer posting at Engramme — free, in seconds.

About the Role

Build and deploy ML models for memory retrieval and contextual understanding. Create scalable ML infrastructure that powers intelligent memory systems.

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
Collaborate with research team to productionize new algorithms

Requirements

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

Skills

Python
ML frameworks (PyTorch, TensorFlow)
MLOps
model serving
monitoring
NLP
embeddings
retrieval systems
cloud platforms (AWS, GCP)
containers
large-scale data processing
large language models
prompt engineering
vector databases (Pinecone, Weaviate, Milvus)
recommendation systems
search
information retrieval
ranking systems
model optimization
quantization
real-time ML systems
transformer architectures

Experience Level

4+ years of ML engineering experience