Senior AI Engineer, NLP & Training Data - 11316

CoupaCoupa·Remote(Flexible / Remote)·Work From Anywhere
AI & Machine Learning
Excel

WFA Digital Insight

The demand for skilled AI engineers with expertise in NLP and training data has surged, driven by the increasing adoption of AI in business decision-making. Coupa, a leader in total spend management, is at the forefront of this trend. With the company's commitment to innovation and collaboration, this role stands out in the remote job market. Candidates should be prepared to showcase their technical skills, particularly in Excel, and their ability to drive impactful business outcomes.

Job Description

About the Role

Coupa's AI platform empowers businesses to make smarter, more profitable decisions through predictive, prescriptive, and automated solutions. As a Senior AI Engineer, NLP & Training Data, you will play a key role in building the data factory that produces high-quality training datasets for model development efforts.

Responsibilities

  • Design and implement training data generation pipelines, including synthetic data generation
  • Build data labeling and annotation workflows with quality validation loops
  • Convert enterprise data into formats suitable for model training
  • Implement active learning strategies to identify high-value training examples
  • Collaborate with domain experts to validate training data quality and relevance

Requirements

  • 5+ years of software engineering experience, with 2+ years in NLP, data science, or ML data engineering
  • Experience with text processing, tokenization, and NLP pipelines
  • Hands-on experience with data labeling tools and annotation workflows
  • Experience generating synthetic training data using language model APIs

How to Stand Out

  • Showcase your proficiency in Excel and AI engineering tools in your resume and cover letter to stand out.
  • Prepare examples of how you've driven business outcomes through data-driven decision-making.
  • Be ready to discuss your experience with NLP pipelines and data labeling tools during the interview.
  • Highlight your ability to collaborate with cross-functional teams, including domain experts.
  • Consider including links to personal projects or contributions to open-source initiatives in your application to demonstrate your skills.

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