Principal Machine Learning Engineer (MLE)
Core
Design, build, deploy, and scale machine learning and generative AI systems for production use cases across multi-cloud environments.
Role type
Principal Machine Learning Engineer (Generative AI & MLOps)
Builds
Production-grade ML and LLM-powered systems, end-to-end ML pipelines, and containerized services.
Domain
Digital Infrastructure, Cloud Computing, Generative AI
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, NLP fundamentals (transformers, embeddings), Cloud platforms (GCP, AWS, Azure), MLOps (CI/CD, model versioning), System design, Docker, Kubernetes, Statistical methods
Preferred skills
Deep learning frameworks (YOLOv7, DDRNet, RFTM), Computer vision, A/B testing, Feature engineering
Technologies
PyTorch, TensorFlow, Docker, Kubernetes, GCP, AWS, Azure, YOLOv7, DDRNet, RFTM
Responsibilities
Design and develop ML/LLM solutions for production; Develop end-to-end ML pipelines from ingestion to monitoring; Architect LLM-powered systems integrating agents across cloud platforms; Optimize ML workflows for performance and cost; Implement MLOps best practices including automated retraining; Deploy and manage models in production with A/B testing.
Seniority
Principal, hands-on IC with strategic impact