Member of Technical Staff, Data Flywheel
New York, NY · San Francisco, CA · London · New York City, New York, United States
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Research — team source
Department: Research
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
Read the full posting
What you’ll work on
Full postingThe Data Flywheel team closes the gap between benchmark performance and useful performance in the real world.
This is a hands-on technical role at the intersection of research and deployment.
Find and assess high-value data sources and partnerships tied to real use cases
Design evaluations, graders, and feedback loops for priority real-world behaviors
Analyze model failure modes and turn them into datasets, reward signals, and training fixes
Run human and synthetic data programs with vendors where existing data falls short
Build pipelines to ingest, inspect, version, and evaluate data at scale
From the employer’s posting
The Data Flywheel team closes the gap between benchmark performance and useful performance in the real world. We identify and build the signals, data, and feedback loops that turn model usage into rigorous evaluations, targeted training data, and measurable improvements in future generations of models.
This is a hands-on technical role at the intersection of research and deployment. You'll take ambiguous model behaviors from first observation through measurement, intervention, and validated improvement, working across evaluation, human and synthetic data, infrastructure, post-training, and live deployments. You'll collaborate closely with researchers and engineers across the company, as well as customers, partners, vendors, and the open-source community.
Identify high-value data sources and partnership opportunities
Design and build evaluations, graders, and feedback loops that make priority real-world model behaviors measurable
Analyze model performance and failure modes, then translate those insights into targeted datasets, reward signals, and training interventions
Develop human and synthetic data strategies for capabilities where existing data is insufficient, including designing and running evaluation and data-collection programs with vendors
Build the infrastructure and pipelines needed to ingest, inspect, version, and evaluate data reliably at scale
Education & alternatives
What We’re Looking For - Degree (BS, MS, or PhD) in Computer Science, Machine Learning, or related discipline, or equivalent practical experience - Deep technical understanding of LLM training and evaluation, with hands-on experience in areas such as evaluation design, data curation, reinforcement learning, or reward design
Benefits in the posting
Full benefits wording- 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.
- 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.
- 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.
From the employer’s posting.
About Reflection
We build open models that let anyone control their intelligence and help shape the future of AI.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 28, 2026 · 63 days ago
- Recorded sightings
- 103
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Aug 25, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Already applied? Track this application
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.
Role Overview
The Data Flywheel team closes the gap between benchmark performance and useful performance in the real world. We identify and build the signals, data, and feedback loops that turn model usage into rigorous evaluations, targeted training data, and measurable improvements in future generations of models.
This is a hands-on technical role at the intersection of research and deployment. You'll take ambiguous model behaviors from first observation through measurement, intervention, and validated improvement, working across evaluation, human and synthetic data, infrastructure, post-training, and live deployments. You'll collaborate closely with researchers and engineers across the company, as well as customers, partners, vendors, and the open-source community.
What You’ll Do
Identify high-value data sources and partnership opportunities, deeply understand the underlying use cases, and translate them into representative evaluations
Bring new data sources online, from initial partner conversations and data scoping through quality validation and integration into production evaluation and training pipelines, where appropriate
Design and build evaluations, graders, and feedback loops that make priority real-world model behaviors measurable
Analyze model performance and failure modes, then translate those insights into targeted datasets, reward signals, and training interventions
Develop human and synthetic data strategies for capabilities where existing data is insufficient, including designing and running evaluation and data-collection programs with vendors
Build the infrastructure and pipelines needed to ingest, inspect, version, and evaluate data reliably at scale
Collaborate closely with pre-training, post-training, applied, and partnership teams to turn new signals into measurable model improvements
What We’re Looking For
Degree (BS, MS, or PhD) in Computer Science, Machine Learning, or related discipline, or equivalent practical experience
Deep technical understanding of LLM training and evaluation, with hands-on experience in areas such as evaluation design, data curation, reinforcement learning, or reward design
Strong software engineering skills and experience building automated data/evaluation pipelines or large-scale ML systems
A track record of owning high-impact projects end to end, navigating ambiguity, and adapting quickly as priorities change
A highly collaborative, action-oriented approach and excitement about defining how a new frontier lab measures and accelerates model progress
High agency and thrive in a fast-paced startup environment; bias for impact over process
Enjoy collaborating across research, engineering, operations, and product disciplines
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.
Equal Employment Opportunity Statement
We are an Equal Opportunity Employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to creating a diverse and inclusive environment and encourage applicants from all backgrounds to apply.
Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York City, New York, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- 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.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.