Machine Learning Engineer
Core
Building and scaling ML infrastructure for AI guardrails, evaluation pipelines, and enterprise-grade deployments.
Role type
Senior Machine Learning Engineer (MLOps)
Builds
Production-ready ML systems, LLMs, RAG pipelines, and detectors
Domain
Enterprise AI safety and regulated environments
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, AWS/GCP/Azure, Kubernetes, Docker, CI/CD, MLflow, W&B, REST/gRPC, FastAPI
Preferred skills
LLMs, RAG systems, distributed training, GPU optimization, open-source contributions
Technologies
PyTorch, TensorFlow, AWS, GCP, Azure, Kubernetes, Docker, MLflow, W&B, FastAPI, gRPC
Responsibilities
Build and maintain robust ML infrastructure (training, serving, monitoring); Deploy LLMs, RAG pipelines, and detectors into production; Translate research prototypes into production APIs; Manage CI/CD pipelines and observability; Optimize for latency, cost, and reliability; Ensure security, compliance, and privacy.
Seniority
Senior, hands-on IC
