Sr. Lead AI Engineer

Coupa Software, Inc. • Foster City, CA

6d • $244,333 - $284,867 • Remote

About The Position

Coupa makes margins multiply through its community-generated AI and industry-leading total spend management platform for businesses large and small. Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers. We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins. At Coupa, we're at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend. We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence. Join a company where your work has a global, measurable impact on our clients, the business, and each other. Coupa already operates production ML models and frontier model integrations across its AI platform. The Sr. Lead Engineer, Machine Learning will own the model training and iteration workstream, building the fine-tuning pipelines, evaluation harnesses, and iterative training loops that take our model capabilities to the next level. Working closely with the Principal Architect, you will turn architecture decisions into production training infrastructure.

Requirements

• 10+ years of software engineering experience, with 4+ years focused on ML/NLP systems.
• Hands-on experience fine-tuning large language models with parameter-efficient methods.
• Strong knowledge of transformer architectures, tokenization, and training optimization.
• Experience building production ML training pipelines with experiment tracking.
• Proficiency in Python, PyTorch, and distributed training frameworks.
• Experience with GPU-based training infrastructure in the cloud.
• Strong evaluation methodology: designing benchmarks, measuring quality, detecting regressions.
• BS/MS in Computer Science, Machine Learning, or equivalent experience.

Nice To Haves

• Experience with RLHF, DPO, or other alignment techniques is a strong plus.

Responsibilities

• Build and own the end-to-end model fine-tuning pipeline: data preprocessing, training, evaluation, and model registry.
• Implement and optimize fine-tuning techniques (QLoRA, LoRA, PEFT, full fine-tune) for our training workloads.
• Design and maintain evaluation harnesses with task-specific benchmarks and automated regression testing.
• Drive the training iteration loop: analyze results, diagnose failure modes, improve data and configuration.
• Implement experiment tracking, hyperparameter optimization, and reproducible training workflows.
• Collaborate on training data strategy with data engineering, including synthetic data generation.
• Evaluate model quality across safety, accuracy, latency, and cost dimensions.
• Contribute to model serving architecture and inference optimization.
• Mentor ML engineers across the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior