Staff ML Engineer: Enterprise AI & Autonomous Systems

Rippling; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Rippling is seeking a Staff Machine Learning Engineer to own the end-to-end ML lifecycle, from problem formulation to production deployment. You will lead ML initiatives across the AI org, shaping models that power Rippling's AI surfaces and platforms.

You will build robust architectures (LLMs, RAG, RLHF), push frontier techniques to production, and mentor engineers while collaborating with Product and Platform teams. This is a hands-on, high-velocity role.

Qualifications

• 8+ years of software engineering with 5+ years in ML
• Expert in LLMs, transformers, RLHF
• Skilled in production ML tooling and data pipelines
• Experience building evaluation systems for generative AI
• Ability to lead cross-functional technical initiatives
• Strong communication with diverse audiences

Responsibilities

• Own the end-to-end ML lifecycle for high-impact AI initiatives
• Design and implement novel ML architectures (LLMs, RAG, reward models)
• Build evaluation infrastructure: offline benchmarks, A/B testing, monitoring
• Lead research-to-production efforts using frontier techniques
• Design self-improving systems with automated retraining pipelines
• Partner with Product and Platform teams
• Mentor engineers on ML best practices
• Track ML research and translate to production systems

Skills

8+ yrs SWE

ML in prod

LLMs & Transformers

PyTorch/JAX

Evaluation systems

Cross-functional leadership

Strong communication

Enterprise data knowledge

Publications a plus

Tools

PyTorch

JAX

Job description

Rippling is seeking a Staff Machine Learning Engineer to own the end-to-end ML lifecycle, from problem formulation to production deployment. You will lead ML initiatives across the AI org, shaping models that power Rippling's AI surfaces and platforms.

You will build robust architectures (LLMs, RAG, RLHF), push frontier techniques to production, and mentor engineers while collaborating with Product and Platform teams. This is a hands-on, high-velocity role.