Evaluation Engineer, Applied AI

The Role

As an Evaluation Engineer on the Applied AI team, you will shape how enterprise customers measure and trust AI solutions. You will work closely with clients and internal stakeholders to deliver evaluation systems that define when an AI model is ready for real business impact. The team's mission is to ensure every project—no matter how ambitious—moves from idea to production with clarity and accountability. Your work will sit at the intersection of research, engineering, and solutions, directly influencing how models are improved and deployed across varied domains.

What You Will Do

• Design and implement comprehensive frameworks to evaluate large language model (LLM) performance across customer use cases

• Build and maintain scalable evaluation infrastructure and pipelines for rapid, reproducible assessment

• Develop new evaluation methods for sector-specific or emerging model capabilities

• Collaborate with customers to create custom evaluation suites that fit their unique needs and criteria

• Partner with research teams to turn evaluation insights into actionable model improvements

• Work with product teams to refine evaluation tooling based on user feedback

• Define and communicate clear success metrics for "production-ready" AI models

• At least 3 years of experience evaluating ML, LLM, or agentic systems

• Proven background in implementing AI or machine learning products, especially with APIs or back-end systems

• Strong Python coding skills

• Deep understanding of machine learning concepts and algorithms, especially as they pertain to LLMs

• Experience communicating technical topics clearly to both technical and non-technical audiences

• Familiarity with evaluation frameworks like LM Eval Harness or OpenAI Evals, or contributions to related open-source projects

• Experience working with ML libraries (e.g., PyTorch, HuggingFace Transformers)

• Collaborative, direct communicator who values outcomes and low-ego teamwork