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# Staff Machine Learning Engineer - AI Cloud

- **Company:** CO-RIPPLING LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Cloud Computing, Graph Database, Machine Learning, Performance Tuning, Tensorflow, Enterprise Data Management, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Transformer Architectures, Machine Learning Operations
- **Published:** November 6, 2026
- **Apply:** https://www.juju.com/job/7_06E487276643496E81BCA4AAB8C12430

## About the Role

engineering experience, with 5+ years focused on ML, shipping ML systems to production at scale Deep expertise in modern ML: LLMs, transformer architectures, fine-tuning, RLHF, RAG Strong fundamentals in classical ML and statistics Hands-on proficiency with ML frameworks (PyTorch, JAX) and production ML infrastructure Experience building evaluation systems for generative AI Proven ability to lead complex, cross-functional technical initiatives Strong product instincts Clear, precise communication to diverse audiences Comfort with ambiguity and high velocity Publications in top ML venues (NeurIPS, ICML, ACL, EMNLP) are a plus Experience with enterprise data or knowledge graphs is a plusAdditional InformationRippling is an equal opportunity employer.

## Description

This is a deeply hands-on role.What you will doOwn the end-to-end machine learning lifecycle for high-impact AI initiatives Design and implement novel ML architectures (fine-tuned LLMs, RAG, reward models, multi-agent orchestration) tailored to Rippling's enterprise domain Build robust evaluation and experimentation infrastructure: offline benchmarks, A/B testing, and continuous monitoring of model quality Develop training pipelines and data flywheels that leverage Rippling's structured data graph Lead research-to-production efforts: identify where frontier techniques (RLHF, distillation, structured decoding, tool-use training) unlock step-function improvements Design self-improving systems: feedback loops, active learning, and automated retraining pipelines Partner closely with Product and Platform teams Mentor engineers across the org on ML best practices Track the frontier of ML research and translate breakthroughs into production systemsWhat you will need8+ years of, software