Our Mission
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.
What You’ll Do:
Design and implement techniques for sourcing, curating, and filtering large-scale web, text, and code data, with opportunities to extend into other modalities as our models evolve.
Develop data quality metrics and analyses that measure coverage, diversity, and representativeness across sources.
Join the pre-training research team to design and run data experiments, working with infrastructure teams to scale the supporting data systems efficiently and reproducibly
Investigate and mitigate data risks, including privacy, safety, and licensing concerns, to support responsible and ethical data use.
Evaluate dataset changes through ablations and scaling experiments, tracing their downstream effects on model learning and behavior.
Publish and present research, and share code, datasets, and insights that move the open AI community forward.
What We're Looking For:
Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch or JAX), with 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 the ability to explain complex technical ideas.
Preferred qualifications (we encourage you to apply even if you don’t meet all of these, but at least some):
A strong grasp of probability, statistics, and ML fundamentals, and the ability to tell real effects from noise and bugs in experimental data.
Experience with curation, preprocessing, and analysis of large-scale text or code datasets; exposure to multimodal data 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.
What We Offer:
We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models.
We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.
Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
Meals: Lunch and dinner are provided in the office daily.
Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
Team building: We have regular off-sites, happy hours, and team celebrations.
Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization.
Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice