Our Mission
Reflections mission is to build open superintelligence and make it accessible to all.
Were developing open weight models for individuals agents enterprises and even nation states. Our team of AI researchers and company builders come from DeepMind OpenAI Google Brain Meta Anthropic and beyond.
About the Role
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures but from better data.
As a member of the Data Team your mission is to build and operate the ingestion systems that turn the open web and other large-scale data sources into reliable well-structured corpora for training frontier models. You will own the machinery that acquires extracts normalizes versions and delivers data to our pre-training pipelines. Youll work directly with world-class researchers to close the loop between what we collect and how it impacts model performance.
This role is ideal for engineers who love building robust distributed systems but who also want to run experiments reason about tradeoffs in data acquisition and iterate quickly based on measurable impact.
Working closely with our pre-training and data quality teams you will:
Build and operate large-scale data ingestion systems for pre-training including web crawling extraction and dataset delivery
Run experiments to evaluate crawling strategies extraction methods and ingestion tradeoffs
Analyze ingested data to identify gaps redundancy and areas to improve
Build ingestion pipelines that scale reliably across large data campaigns
Develop specialized crawlers for high-priority data sources
Review code debug production issues and continuously improve ingestion infrastructure
About You:
Curious about how training data influences model capabilities and can iterate quickly based on measurable downstream impact
Able to collaborate tightly across functions: researchers infra operations and external partners.
Enjoy working in a hybrid researchengineering role
Skills and Qualifications:
Experience building web crawling data ingestion or large-scale data acquisition systems using Ray Beam Spark or similar technologies.
Familiarity with how LLMs are trained and evaluated and an intuition for what makes data useful for training
Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable testable and maintainable
Comfortable designing experiments and using data to guide system improvements
Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly
What We Offer:
We believe that to build superintelligence that is truly open you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company and help define the frontier 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 the best talent globally.
Health & wellness: Comprehensive medical dental vision life and disability insurance.
Life & family: Fully paid parental leave for all new parents including adoptive and surrogate journeys. Financial support for family planning.
Benefits & balance: paid time off when you need it relocation support and more perks that optimize your time.
Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
Required Experience:
Staff IC
Our MissionReflections mission is to build open superintelligence and make it accessible to all.Were developing open weight models for individuals agents enterprises and even nation states. Our team of AI researchers and company builders come from DeepMind OpenAI Google Brain Meta Anthropic and bey...
Our Mission
Reflections mission is to build open superintelligence and make it accessible to all.
Were developing open weight models for individuals agents enterprises and even nation states. Our team of AI researchers and company builders come from DeepMind OpenAI Google Brain Meta Anthropic and beyond.
About the Role
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures but from better data.
As a member of the Data Team your mission is to build and operate the ingestion systems that turn the open web and other large-scale data sources into reliable well-structured corpora for training frontier models. You will own the machinery that acquires extracts normalizes versions and delivers data to our pre-training pipelines. Youll work directly with world-class researchers to close the loop between what we collect and how it impacts model performance.
This role is ideal for engineers who love building robust distributed systems but who also want to run experiments reason about tradeoffs in data acquisition and iterate quickly based on measurable impact.
Working closely with our pre-training and data quality teams you will:
Build and operate large-scale data ingestion systems for pre-training including web crawling extraction and dataset delivery
Run experiments to evaluate crawling strategies extraction methods and ingestion tradeoffs
Analyze ingested data to identify gaps redundancy and areas to improve
Build ingestion pipelines that scale reliably across large data campaigns
Develop specialized crawlers for high-priority data sources
Review code debug production issues and continuously improve ingestion infrastructure
About You:
Curious about how training data influences model capabilities and can iterate quickly based on measurable downstream impact
Able to collaborate tightly across functions: researchers infra operations and external partners.
Enjoy working in a hybrid researchengineering role
Skills and Qualifications:
Experience building web crawling data ingestion or large-scale data acquisition systems using Ray Beam Spark or similar technologies.
Familiarity with how LLMs are trained and evaluated and an intuition for what makes data useful for training
Comfortable working with very large datasets (multi-TB to PB scale) and building systems that are observable testable and maintainable
Comfortable designing experiments and using data to guide system improvements
Excellent communication skills. You can explain system behavior. You consider and communicate tradeoffs clearly
What We Offer:
We believe that to build superintelligence that is truly open you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company and help define the frontier 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 the best talent globally.
Health & wellness: Comprehensive medical dental vision life and disability insurance.
Life & family: Fully paid parental leave for all new parents including adoptive and surrogate journeys. Financial support for family planning.
Benefits & balance: paid time off when you need it relocation support and more perks that optimize your time.
Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
Required Experience:
Staff IC
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