Staff ML Engineer — Enterprise AI & Self-Improving Systems

Rippling; Seattle (WA); On-site; USD 198,000 - 330,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Rippling is seeking a Staff Machine Learning Engineer to own the end-to-end ML lifecycle and lead production ML initiatives across the Rippling AI stack. You will shape problem formulation, data strategy, model development, evaluation, and deployment for high-impact enterprise AI projects.

You will join the team behind Rippling AI, building autonomous ML systems that power multiple product surfaces with reliable, scalable models, in a fast-paced, highly collaborative environment.

Qualifications

• 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.
• Publications in top ML venues are a plus.
• Experience with enterprise data or knowledge graphs is a plus.

Responsibilities

• Own the end-to-end machine learning lifecycle for high-impact AI initiatives.
• Design and implement novel ML architectures tailored to enterprise domain.
• Build evaluation and experimentation infrastructure, including offline benchmarks and A/B testing.
• Lead research-to-production efforts to unlock step-function improvements.
• Design self-improving systems with feedback loops and automated retraining pipelines.
• Partner closely with Product and Platform teams.

Skills

ML engineering

LLMs

Transformer models

RLHF

RAG

PyTorch

JAX

Tools

PyTorch

JAX

Job description

Rippling is seeking a Staff Machine Learning Engineer to own the end-to-end ML lifecycle and lead production ML initiatives across the Rippling AI stack. You will shape problem formulation, data strategy, model development, evaluation, and deployment for high-impact enterprise AI projects.

You will join the team behind Rippling AI, building autonomous ML systems that power multiple product surfaces with reliable, scalable models, in a fast-paced, highly collaborative environment.