Original listing text, shown exactly as published by the company.
What You’ll Do
- Lead the strategy, design, and delivery of AI/ML models (including Generative AI use cases) across multiple product domains.
- Establish and scale MLOps practices to enable reliable, reproducible, and efficient model development and deployment.
- Define and operationalize golden datasets, including data curation, labeling standards, and evaluation frameworks.
- Own model performance: define KPIs, implement continuous evaluation, and drive ongoing improvements in accuracy, robustness, and latency.
- Build and advance AI observability, monitoring, and feedback loops to ensure model transparency and trust.
- Partner cross-functionally with Engineering, Product, Data, and Platform teams to integrate AI into production systems and user experiences.
- Establish and enforce Responsible AI practices, including fairness, bias mitigation, explainability, and compliance.
- Lead, mentor, and grow a high-performing global team of data scientists and ML engineers.
- Influence executive stakeholders by translating complex AI concepts into clear business impact and strategy.
What You Will Bring to Coupa
- 10+ years of experience in Data Science, Machine Learning, or AI, with 3–5+ years in leadership roles managing high-performing teams.
- Strong expertise in machine learning, deep learning, and statistical modeling, with experience in production environments.
- Proven track record of delivering scalable, production-grade AI systems that drive measurable business impact.
- Hands-on experience with modern MLOps ecosystems (e.g., SageMaker, Vertex AI, Databricks, Kubeflow, MLflow).
- Deep experience with data strategy, including dataset creation, labeling, governance, and evaluation methodologies.
- Familiarity with Generative AI / LLMs, prompt engineering, fine-tuning, and evaluation techniques.
- Strong programming skills in Python and experience with frameworks such as TensorFlow, PyTorch, or similar.
- Excellent leadership, communication, and stakeholder management skills.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field (PhD preferred).
