Research Scientist

About the company Our client is a fast-growing technology company. The role Raydar is recruiting for this role on behalf of our client. Lead applied research on how machine learning models are measured and improved, with a focus on the quality of the data behind them. You will join early as a founding member of a small research function and set direction with a high degree of independence, partnering closely with subject-matter specialists. What you'll do - Create and maintain benchmarks, test suites and dataset classification schemes that establish quality standards. - Run independent investigations and publish findings to build the company's visibility in the research community. - Pinpoint weaknesses in current language models and assemble datasets that address them. - Collaborate with domain specialists and delivery colleagues to describe what excellent training and testing data looks like in different fields. - Shape the research roadmap, proposing ideas, designing experiments and rallying colleagues around them. Requirements What we're looking for - About 5 or more years of research experience across academic and industry settings. - A PhD in machine learning, computer science, statistics or a quantitative discipline from a leading program. - A strong publication record at top machine learning conferences, in a lead or near-lead author role. - Direct, full-cycle ownership of post-training work for large language models. - Deep knowledge of model assessment, benchmark creation and data quality as they feed into model training. - Prior research work in a corporate AI environment, such as a model developer or AI tooling provider. - A research specialty in language model training or post-training, rather than speech, audio, vision or robotics. - Skill in designing experiments, examining data and delivering quantitative analysis from start to finish. - Curiosity about how models behave and the ability to suggest data-driven remedies for their shortcomings. - Willingness to work on-site 5 days per week, with some flexibility to 4. Bonus points - A master's degree combined with an outstanding body of published work may be considered in place of a PhD. - Comfort with Python and PyTorch for working alongside engineers on evaluation tooling. Benefits Compensation and benefits - Base salary: USD 250,000 to 350,000 per year - Equity Location and work model - New York, NY or San Francisco, CA, United States - Hybrid: 5 days in-office, flexible to 4 days - Full-time