# Member of Technical Staff, Human Data Quality Engineer at Reflectionai > Onsite · United States · Staff · QA / Test · open. Source: https://alderhq.app/jobs/ashby%3Areflectionai%3Ac567de5a-a599-42f7-8f74-602fab95fd17 (read 2026-11-07). ## Facts (observed) - Company: [Reflectionai](https://alderhq.app/companies/reflectionai) - Location text: San Francisco, CA; London; New York, NY - Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco, CA; London; New York, NY") - Posted: 2026-01-08 (303 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/reflectionai/c567de5a-a599-42f7-8f74-602fab95fd17 - Skills listed (inferred): Python, LLMs ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (SF Bay Area, n 12): p25 $170k, median $190k, p75 $210k ## Description (the employer's text) ### 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Areflectionai%3Ac567de5a-a599-42f7-8f74-602fab95fd17 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.