Research Scientist

The Expert Data-as-a-Service (DaaS) team delivers high-quality, large-scale datasets that power frontier AI systems. As a researcher working on DaaS, you will focus on developing novel approaches for data generation, curation and evaluation. You will be responsible for designing innovative techniques that combine automated methods with human expertise to achieve best-in-class efficiency and quality. You will collaborate closely with engineering and operations teams, as well as our customers’ research teams,  to define the future of data generation workflows that will power frontier AI models.

• Conduct research on data curation and generation to support emerging use cases across domains
• Collaborate with customer research teams to translate their high-level goals into data requirements, and annotation guidelines and workflows
• Design and prototype data generation and curation pipelines that feed directly into Data as a Service offerings
• Build sophisticated evaluators to measure quality in our data, including coverage, bias, and utility
• Write clear, maintainable Python code to support experiments and production pipelines; contribute to internal tooling and shared libraries
• Iterate rapidly on solutions based on customer feedback, emerging research, and evolving DaaS requirements
• Collaborate cross-functionally with delivery managers, vendors, and engineering teams to research to production

• PhD. in Computer Science or a related field with focus on data centric AI and synthetic data generation
• Strong foundation in large language models, generative AI, or data generation techniques, especially for supervised fine-tuning and reinforcement learning
• Experience developing, experimenting with, and deploying AI models and data pipelines at scale
• Solid programming skills in Python; familiarity with ML frameworks such as PyTorch, HuggingFace, etc. And familiarity with software engineering best practices and clean coding.
• Track record of working in fast paced, iterative environments and handling uncertainty in project requirements
• Bias for action, comfortable rolling up your sleeves, experimenting, and iterating quickly to solve problems
• Strong communication and collaboration skills, especially when working across research, engineering, and delivery teams

• Past experience in data labeling, annotation, or curation projects
• Publications or contributions related to data curation for LLM fine tuning
• Knowledge of production workflows for DaaS offerings or data delivery teams
• Familiarity with quality control processes for high volume data pipelines

• Be part of a growing Data as a Service business that powers frontier AI models for top enterprises
• Work at the intersection of research and production, bringing novel data generation and curation techniques into real world pipelines
• Collaborate with a founder stage DaaS team, contributing to development of processes, tooling, and quality standards
• Competitive compensation range of $140,000 – $275,000 plus equity opportunities
• Growth oriented environment where your work directly impacts product direction and customer success

Learn more about our recent launch in Forbes: Snorkel AI Raises $100 Million to Build Better Evaluators for AI Models`

Explore our Expert Data as a Service offering: snorkel.ai/expert-data-as-a-service

This role is ideal for candidates who love both research and building real AI systems in a dynamic, high impact setting. A PhD in machine learning or related field with a strong publication record is preferred, but we also welcome applications from those with equivalent expertise gained through industry experience, research labs, or other career paths.