Job Description :

Function : Data Science and Analysis ? Data Science / Machine Learning

Machine LearningLLMsNLPGenerative AIPrompt EngineeringOpenAI

Responsibilities :

- You define gold-standard evaluation datasets and metrics that internal teams adopt as a standard.

- You ship datasets and pipelines that are statistically rigorous, reproducible, and scalable.

- You elevate the organization's ML practice by embedding sound statistical and scientific methodology into product and engineering work.

- You are recognized as a thought leader who sets strategy while still contributing technically in depth.

Requirements :

Education : Master's degree (PhD preferred) in Computer Science, Statistics, Machine Learning, or a related quantitative field.

- Strong background in mathematical and statistical foundations of machine learning (probability, linear algebra, optimization, experimental design).

- Demonstrated experience in end-to-end ML lifecycle : dataset preparation, model training, evaluation, deployment, and monitoring.

- Proven expertise in evaluation dataset design and metric creation, not just using existing benchmarks but knowing when and how to improve them.

- Experience with LLM evaluation, fine-tuning, and RAG, with the engineering skills to build production-ready pipelines.

- Track record of strategic impact at a staff or principal level, setting evaluation and research standards across teams.

Even better if you have :

- Publications, open-source contributions, or widely adopted benchmarks in ML/AI.

- Prior experience shaping AI evaluation frameworks at an organizational or industry level.

- Comfort working at the interface of science, engineering, and product.