Member of Technical Staff - Pre-Training Data

Reflection • San Francisco, CA

6d

About The Position

Reflection is a research lab focused on making intelligence open and accessible through open models that people can control, customize, and build on. The Member of Technical Staff - Pre-Training Data joins the pre-training research team to develop data sourcing, curation, filtering, and evaluation approaches for large-scale model training. The work currently focuses on web, text, and code data, with potential to extend to other modalities as models evolve.

The role combines data research and engineering: developing quality metrics and analyses, running data experiments with research and infrastructure teams, scaling reproducible data systems, and assessing how dataset changes affect model learning and behavior. It also involves investigating privacy, safety, and licensing risks, and contributing research, code, datasets, and insights to the open AI community.

Reflection describes itself as a talent-dense team building from the ground up. The company offers salary and equity, stock options, comprehensive medical, dental, vision, and life coverage, an annual wellness allowance, daily office meals, paid parental leave, paid time off, visa sponsorship, and regular team events. This position may involve access to technology or source code subject to U.S. export control laws; an offer may depend on the Company's ability to provide compliant access. Applicant personal data is processed as described in the Candidate and Employee Privacy Notice.

Requirements

• Proficiency in Python.
• Familiarity with at least one deep learning framework, such as PyTorch or JAX.
• Experience debugging distributed workloads and writing code that scales.
• Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline, with strong theoretical and empirical grounding.
• Clear written communication and ability to explain complex technical ideas.

Nice To Haves

• Strong grasp of probability, statistics, and machine learning fundamentals, and ability to distinguish real effects from noise and bugs in experimental data.
• Experience curating, preprocessing, and analyzing large-scale text or code datasets; multimodal data exposure is a plus.
• Background in data engineering, dataset construction, or large-scale web data processing for machine learning.
• Experience evaluating or improving training data quality, and knowledge of data ethics, safety, and licensing frameworks relevant to AI datasets.
• Contributions to open datasets, research publications, or data tooling.
• PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline, or equivalent industry research experience.

Responsibilities

• Design and implement techniques for sourcing, curating, and filtering large-scale web, text, and code data, with potential to extend to other modalities.
• Develop data quality metrics and analyses to measure source coverage, diversity, and representativeness.
• Design and run data experiments as part of the pre-training research team, working with infrastructure teams to scale data systems efficiently and reproducibly.
• Investigate and mitigate data risks, including privacy, safety, and licensing concerns.
• Evaluate dataset changes using ablations and scaling experiments, and trace their downstream effects on model learning and behavior.
• Publish and present research, and share code, datasets, and insights with the open AI community.

Benefits

• Top-tier compensation with salary and equity structured to recognize and retain talent globally.
• Stock options for employees.
• Comprehensive medical, dental, vision, and life coverage.
• Annual wellness allowance.
• Lunch and dinner provided daily in the office.
• 22 weeks of paid parental leave for new birthing and non-birthing parents, including adoptive and surrogate journeys.
• Unlimited paid time off in the U.S. and 30 vacation days in the U.K.
• Visa sponsorship and support for long-term immigration pathways where applicable.
• Regular off-sites, happy hours, and team celebrations.

What This Job Offers

• Job Type: Full-time