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  • Reflection

    Member of Technical Staff, Human Data Quality Engineer

    Reflection · 🇺🇸 San Francisco, CA · posted today
    ApplyFull posting

    Extracted from the posting

    Base
    Not stated
    Remote
    On-site
    Visa
    We sponsor visas to help exceptional talent join our team
    Stack
    Python

    TL;DR

    Own upstream data quality for LLM post-training and evaluation by analyzing expert-developed datasets and defining quality standards for reasoning, alignment, and agentic use cases. Build and scale automated QA pipelines, including LLM-as-a-Judge frameworks, and give feedback to external data vendors. Works with the post-training research teams; stack is Python and ML/LLM workflows.

    About Reflection →

    The full posting

    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

    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 ensure that the data used to train and evaluate our models meets a high bar for quality, reliability, and downstream impact. You will directly shape how our models perform on critical capabilities — agentic tool use, long-horizon reasoning and robust safety alignment.

    Working with world-class researchers on our post-training teams, you’ll help turn fuzzy notions of “good data” into concrete, measurable standards that scale across large data campaigns. We’re looking for engineers who combine strong engineering fundamentals with a deep curiosity about data quality and its impact on model behavior


    Working closely with our post-training teams you will:

    • Own upstream data quality for LLM post-training and evaluation by analyzing expert-developed datasets and operationalizing quality standards for reasoning, alignment, and agentic use cases
    • Partner closely with research and post-training teams to translate requirements into measurable quality signals, and provide actionable feedback to external data vendors
    • Design, validate, and scale automated QA methods, including LLM-as-a-Judge frameworks, to reliably measure data quality across large campaigns
    • Build reusable QA pipelines that reliably deliver high-quality data to post-training teams for model training and evaluation
    • Monitor and report on data quality over time, driving continuous iteration on quality standards, processes, and acceptance criteria


    About You

    • Strong engineering fundamentals with experience building data pipelines, QA systems, or evaluation workflows for post-training data and agentic environments
    • Detail-oriented with an analytical mindset, able to identify failure modes, inconsistencies, and subtle issues that affect data quality
    • Solid understanding of how data quality impacts training (SFT and RL) and evaluation, with the ability to translate quality concerns into concrete signals, decisions, and feedback
  • Experience designing and validating automated quality checks, including rule-based systems, statistical methods, or model-assisted approaches such as LLM-as-a-Judge
  • Comfortable working autonomously, owning problems end-to-end, and collaborating effectively with researchers, engineers, and operations partners

  • Skills and Qualifications

    • Proficiency in Python and building ML / LLM workflows. Must be comfortable debugging and writing scalable code
    • Experience working with large datasets and automated evaluation or quality-checking systems
    • Familiarity with how LLMs work and can describe how models are trained and evaluated
    • Excellent communication skills with the ability to clearly articulate complex technical concepts across teams

    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
    Reflection AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, ancestry, age, marital status, disability, genetic information, veteran or military status, or any other characteristic protected by applicable law. We encourage applicants from all backgrounds to apply.

    We provide reasonable accommodations throughout the hiring process for applicants with disabilities, pregnancy-related limitations, or religious needs. If you need an accommodation, contact us at [email protected].

    We will consider for employment qualified applicants with arrest and conviction records in accordance with applicable law, including the San Francisco Fair Chance Ordinance and the California Fair Chance Act.


    Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice