Data-Driven LLM Research Scientist

Reinforced Learning; Town of Tonawanda (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

Reinforced Learning in the United States seeks a researcher to design and run training experiments that isolate how datasets affect model behavior, including supervised fine-tuning (SFT) and RL-based post-training, measuring improvements under varied conditions.

You will collaborate with partner labs, publish external-facing research, and iterate on data quality based on results to demonstrate clear evidence of data-driven improvements.

Qualifications

• Strong familiarity with LLM training and evaluation methodologies.
• Ability to design lightweight experiments, move fast, and extract actionable insights from messy results.
• Comfort working across domains (finance, software engineering, policy, and more).
• Bias toward building over theorizing.

Responsibilities

• Run controlled SFT and RL experiments to measure the impact of datasets on model performance.
• Help build public evals and new data types that push the frontier.
• Publish external-facing research, blog posts, and technical reports.
• Work with internal SPLs to iterate on data quality based on results.

Skills

LLM training

Experiment design

Cross-domain experience

Data quality focus

Education

Bachelor’s degree (or equivalent)

Master’s by research

Job description

Reinforced Learning in the United States seeks a researcher to design and run training experiments that isolate how datasets affect model behavior, including supervised fine-tuning (SFT) and RL-based post-training, measuring improvements under varied conditions.

You will collaborate with partner labs, publish external-facing research, and iterate on data quality based on results to demonstrate clear evidence of data-driven improvements.