# Staff Machine Learning Engineer

**Company:** [Rippling](https://hotfix.jobs/companies/rippling)
**Location:** San Francisco, CA, New York, NY, Seattle, WA
**Role:** ML Engineering
**Salary:** $198k – $330k/yr
**Experience:** 8+ years
**Skills:** Machine Learning, LLMs, Transformers, Fine-Tuning, RLHF, RAG, PyTorch, JAX, Evaluation Systems, Generative AI, Multi-Agent Orchestration, Production Ml Infrastructure
**Posted:** 2026-07-06

> Staff ML Engineer owning end-to-end lifecycle for enterprise AI at Rippling: design novel architectures (LLMs, RAG, RLHF), build evaluation and self-improving systems, and ship production ML leveraging proprietary data graph. Requires 8+ years engineering with 5+ in ML.

## Job Description

## Responsibilities
- Own 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 systems.

## Requirements
- 8+ years of software 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.

## Nice-to-Haves
- Publications in top ML venues (NeurIPS, ICML, ACL, EMNLP).
- Experience with enterprise data or knowledge graphs.

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**Apply:** https://hotfix.jobs/jobs/90625f55-fa77-4e5f-80c0-02cf87cb8e50
**Canonical:** https://hotfix.jobs/jobs/90625f55-fa77-4e5f-80c0-02cf87cb8e50