Senior Machine Learning Engineer - AI Cloud

Sourced from jobtarget.com

Rippling is hiring a Senior Machine Learning Engineer for its AI Cloud team to build the intelligence layer powering enterprise AI products. You will own the end-to-end ML lifecycle, from problem formulation and data preparation through model development, evaluation, and production deployment. The role focuses on fine-tuned LLMs, RAG, reward models, and multi-agent orchestration tailored to Rippling's proprietary data graph.

• Own the end-to-end ML lifecycle for high-impact AI projects, from problem definition to production deployment
• Design and implement ML systems including fine-tuned LLMs, RAG, reward models, and multi-agent orchestration
• Build evaluation and experimentation capabilities: offline benchmarks, A/B testing, and continuous model quality monitoring
• Develop training pipelines and data flywheels leveraging Rippling's structured data graph
• Take ML techniques from research to production, including RLHF, distillation, structured decoding, and tool-use training
• Build feedback loops, active learning workflows, and automated retraining pipelines
• Partner with Product and Platform teams to translate requirements into reliable ML systems
• Contribute to design and code reviews, share ML best practices, and mentor engineers

• 5+ years of software engineering experience, including 3+ years focused on ML
• Experience shipping and operating ML systems in production
• Strong practical experience with LLMs, transformer architectures, fine-tuning, and RAG
• Familiarity with RLHF or related model-alignment techniques
• Strong fundamentals in classical ML and statistics
• Hands-on proficiency with PyTorch or JAX and production ML infrastructure
• Experience building evaluation systems for generative AI
• Ability to independently deliver complex ML projects and collaborate across functions
• Clear, precise communication and comfort with ambiguity

• Publications in top ML venues (NeurIPS, ICML, ACL, EMNLP)
• Experience with enterprise data or knowledge graphs