Impactful Research Scientist: Data & Evaluation

bareinsights; Los Angeles (CA); On-site; USD 110,000 - 150,000; Full time

Job summary

bareinsights is seeking a Research Scientist to bridge data design and model development for AI training datasets. You will shape evaluation frameworks, define data structures, and run experiments that drive model alignment across finance, code, and enterprise domains.

Based on your background, you will contribute to quantitative measures of dataset quality and collaborate with lab researchers to translate training objectives into concrete data specifications. On-site in Los Angeles.

Qualifications

• Undergraduate or master’s research background; strong preference for candidates who have not yet completed a PhD.
• Prior experience with evals or benchmarking — through academic research, a competing data company, or an internship at an RL environment company.
• Genuine curiosity about how data structure, selection, and quality drive model behavior.
• Ability to design lightweight experiments, move quickly, and extract actionable insights from noisy results.
• Strong quantitative instincts and familiarity with LLM training pipelines, RLHF, RLVR, or evaluation methodology.
• Comfort working across domains including finance, software engineering, and policy.
• Software engineering experience is a meaningful plus — technical depth is valued here.

Responsibilities

• Design data structures that expose meaningful model failure modes across domains such as finance, code, and enterprise workflows.
• Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines.
• Model annotator behavior and run targeted experiments to improve model capabilities.
• Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment.
• Partner with lab research teams to translate training objectives into concrete data and evaluation specifications.

Job description

bareinsights is seeking a Research Scientist to bridge data design and model development for AI training datasets. You will shape evaluation frameworks, define data structures, and run experiments that drive model alignment across finance, code, and enterprise domains.

Based on your background, you will contribute to quantitative measures of dataset quality and collaborate with lab researchers to translate training objectives into concrete data specifications. On-site in Los Angeles.