Companies › Coupa › Senior AI Engineer, NLP & Training Data - 11316

About the role

Coupa · Remote
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.

Why join Coupa?

🔹 Pioneering Technology: 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.
🔹 Collaborative Culture: We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence.
🔹 Global Impact: Join a company where your work has a global, measurable impact on our clients, the business, and each other. 

Learn more on Life at Coupa blog and hear from our employees about their experiences working at Coupa. 

The Impact of a Senior AI Engineer, NLP & Training Data at Coupa: 

Coupa already operates production ML models and frontier model integrations across its AI platform. The Sr. Engineer, AI / 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.

What You’ll Do

  • 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 You Will Bring to Coupa

  • 5+ years of software engineering experience, with 2+ 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.
  • Experience with RLHF, DPO, or other alignment techniques is a strong plus.
  • BS/MS in Computer Science, Machine Learning, or equivalent experience.
    • Coupa complies with relevant laws and regulations regarding equal opportunity and offers a welcoming and inclusive work environment. Decisions related to hiring, compensation, training, or evaluating performance are made fairly, and we provide equal employment opportunities to all qualified candidates and employees. 

    Please be advised that inquiries or resumes from recruiters will not be accepted.

    By submitting your application, you acknowledge that you have read Coupa’s Privacy Policy and understand that Coupa receives/collects your application, including your personal data, for the purposes of managing Coupa's ongoing recruitment and placement activities, including for employment purposes in the event of a successful application and for notification of future job opportunities if you did not succeed the first time. You will find more details about how your application is processed, the purposes of processing, and how long we retain your application in our Privacy Policy.
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