Forward Deployed Researcher (Data as a Service)

Join Snorkel AI as a Forward Deployed Researcher, where you'll partner with frontier AI labs to tackle their most challenging data problems. In this high-impact, customer-facing role, you'll design complex data and environments that improve model performance, serve as a thought partner throughout the engagement, and own a technical domain end to end. You'll work at the intersection of research, technical strategy, and customer partnership, and stay current on frontier AI research and evaluation methodologies.

- Collaborer avec les équipes de recherche des clients pour concevoir des données complexes et des environnements qui améliorent les performances des modèles. - Diriger les conversations techniques avec les chercheurs clients pour comprendre les capacités des modèles, les modes de défaillance, les exigences en matière de données et les critères de succès. - Développer des spécifications techniques pour des projets de données qui équilibrent la rigueur de la recherche et la faisabilité opérationnelle.

- This is a high-impact, customer-facing role that combines deep technical and research credibility with the ability to work directly with customer research teams - Forward Deployed Researchers own a technical domain. You are the person who knows where frontier models fail in it, what data moves those numbers, and what we should build next - Proficiency in Python, familiarity with ML frameworks and LLM APIs, and comfort running evaluations in containerized environments - Ability to work in a fast-moving environment, comfortable with ambiguity and rapid iteration - Willingness to make and state a defensible assumption when a request arrives underspecified, rather than waiting for the customer to close the gap - B.S. in Computer Science, Machine Learning, or related field with 4+ years of experience in AI/ML research or technical roles; advanced degree preferred - Excellent communication skills, ability to deliver technical presentations and explain complex concepts to diverse audiences - Familiarity with data curation workflows, synthetic data generation, LLM-as-a-Judge, or evaluation framework design - Strong expertise in frontier AI concepts including LLMs, training data pipelines, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments - Experience in applied ML research, data science, or research-intensive technical roles - Customer-facing or collaborative research experience, or demonstrated aptitude for client engagement