Job description

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. ABOUT THE ROLE - Research and build solutions across algorithms, scaling laws, data processing, optimizers, and model architecture. - Design and run scientific experiments to advance our understanding of scaling large language models and data efficiency. - Implement state-of-the-art methods from the deep learning literature. - Lead small research projects independently while collaborating on larger initiatives - Optimize the training infrastructure for efficient scaling. - Contribute across the entire stack, from low-level optimizations to high-level model design. ABOUT YOU - Graduate degree (MS or PhD) in Computer Science, Machine Learning, or related discipline. - Solid software engineering capabilities with experience building large-scale systems. - Experience with large-scale ETL workflows and training data preparation. - Deep understanding of large-scale ML, especially as it relates to language models, distributed training, and scaling. - Proficient in Python and deep learning frameworks (PyTorch preferred). - Navigate trade-offs between research objectives and practical engineering realities. - Thrive in a fast-paced, high-agency startup environment with bias toward action. - Strong communication capabilities and comfort working collaboratively. - Passionate about advancing the frontier of intelligence. 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 cdn.sanity.io

Requirements

Must-haves

Research and build solutions across algorithms, scaling laws, data processing, optimizers, and model architecture.
Design and run scientific experiments to advance our understanding of scaling large language models and data efficiency.
Implement state-of-the-art methods from the deep learning literature.
Lead small research projects independently while collaborating on larger initiatives
Optimize the training infrastructure for efficient scaling.
Contribute across the entire stack, from low-level optimizations to high-level model design.
Graduate degree (MS or PhD) in Computer Science, Machine Learning, or related discipline.
Solid software engineering capabilities with experience building large-scale systems.
Experience with large-scale ETL workflows and training data preparation.
Deep understanding of large-scale ML, especially as it relates to language models, distributed training, and scaling.
Navigate trade-offs between research objectives and practical engineering realities.
Thrive in a fast-paced, high-agency startup environment with bias toward action.
Strong communication capabilities and comfort working collaboratively.
Passionate about advancing the frontier of intelligence.

Nice-to-haves

Proficient in Python and deep learning frameworks (PyTorch preferred).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Parental Leave

Wellness