LLM Data Researcher

Summary

Join Turing, a rapidly growing AI company, as a data-savvy leader to evaluate data quality and its impact on model performance. This high-leverage role focuses on maximizing client impact through smarter data practices. You will define and implement strategies to assess data ROI, build and maintain performance benchmarks, and collaborate with cross-functional teams. Responsibilities include developing data evaluation systems, driving quality processes, identifying data gaps, and translating research insights into client value. The ideal candidate possesses a strong grasp of LLMs and data-model dynamics, a proven track record in benchmark development, and experience designing and interpreting performance metrics. This is a full-time remote opportunity with flexible working hours.

Requirements

• Strong grasp of LLMs and data-model dynamics (but this is not a model training role)
• Knowledge of the latest trends in Generative AI and data that is useful for improving foundation models
• Proven track record in benchmark development, model evaluation, or data-centric infrastructure
• Strategic thinker with a bias toward impact: can connect data quality work directly to client value
• Experience designing and interpreting metrics that inform delivery performance
• Familiarity with annotation workflows, validation processes, and scalable QA systems
• Solid ML or data science foundation—able to reason about training impact from a data point-of-view

Responsibilities

• Define and implement strategies to assess the ROI of data across training and fine-tuning pipelines
• Build and maintain benchmarks that measure performance across key client and internal objectives
• Collaborate with data operations, research, and delivery teams to align on quality standards and data priorities
• Develop systems and tooling for continuous data evaluation—measuring what matters, where it matters
• Drive human-in-the-loop quality processes including pre-delivery validation and annotation feedback loops
• Identify data gaps and lead targeted acquisitions or refinements, guided by performance metrics
• Define and/or leverage comprehensive task taxonomy frameworks to structure data annotation efforts and improve training signal quality
• Translate research insights and data evaluations into client-facing value through better delivery and prioritization

Preferred Qualifications

• Experience with feedback-driven annotation loops and pre-delivery QA
• Hands-on experience with taxonomy frameworks and structured data labeling
• Background in data-centric AI or related research, Linguistics as applied to data annotation efforts, or related fields

Benefits

• Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
• Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
• Competitive compensation
• Flexible working hours
• Full-time remote opportunity