Crystal Equation
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Data Analyst I
Onsite
Summary:
Despite rapid advancements in generative AI, achieving high-quality generation remains a challenge. This is primarily due to the scarcity of high-quality training data and the lack of reliable and robust evaluation metrics that can effectively capture subtle details in model outputs, which can significantly impact user experience.
Our team is dedicated to developing comprehensive data curation and evaluation solutions to enhance our model across various quality dimensions. These include visual quality, prompt adherence, identity preservation, naturalness, and visual text generation, among others. We employ diverse approaches, such as sourcing billions of images and identifying suitable ones through a combination of manual annotations and signals from machine learning models. We also utilize both manual and automated evaluation methods to pinpoint quality gaps and data requirements.
Responsibilities:
Annotations:
Skills:
Education/Experience:
Additional Requirements:
Pay range is $40 - $45 per hour with full benefits available, including paid time off, medical/dental/vision/life insurance, 401K, parental leave, and more. Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
THE PROMISES WE MAKE:
At Crystal Equation, we empower people and advance technology initiatives by building trust. Your recruiter will prep you for the interview, obtain feedback, guide you through any necessary paperwork and provide everything you need for a successful start. We will serve to empower you along the way and provide the path for your professional journey.
For more information regarding our Privacy Policy, please visit crystalequation.com/privacy.
Data Analyst I
1 Hacker Way Menlo Park, CA 94025 US
Posted: 01/23/2026
2026-01-23
2026-03-10
Job Number: 41788
Job Description
Data Analyst I
Onsite
Summary:
Despite rapid advancements in generative AI, achieving high-quality generation remains a challenge. This is primarily due to the scarcity of high-quality training data and the lack of reliable and robust evaluation metrics that can effectively capture subtle details in model outputs, which can significantly impact user experience.
Our team is dedicated to developing comprehensive data curation and evaluation solutions to enhance our model across various quality dimensions. These include visual quality, prompt adherence, identity preservation, naturalness, and visual text generation, among others. We employ diverse approaches, such as sourcing billions of images and identifying suitable ones through a combination of manual annotations and signals from machine learning models. We also utilize both manual and automated evaluation methods to pinpoint quality gaps and data requirements.
Responsibilities:
- Data Curation: Manage data labeling workflows, including data enqueueing for labeling, UI for labeling, and extracting labels into datasets for the modeling team.
- Data Engineering (Pipelines): Maintain large-scale, efficient, and reliable data processing pipelines (billions of images). This includes data sourcing, running machine learning models to understand content, and using LLMs to clean data.
- Data Engineering (Governance): Maintain our portfolio of datasets, ensuring governance of access, retention, and privacy compliance.
Annotations:
- Spend time manually annotating training data based on modeling team requirements.
- Use of LLMs and other models to annotate training data or to evaluate generated content. Then apply auditing to understand these model performance.
- Analysis: Collaborate with engineers to identify and summarize model gaps based on evaluations. Utilize these findings to identify necessary data, and then mine and prepare that data for subsequent model training iterations.
- Auditing: Scale validated evaluation protocols with PDO teams, including coordination and auditing. Also, audit and correct human-labeled data.
Skills:
- Verbal and written communication skills, problem solving skills, and interpersonal skills.
- Attention to details and an aptitude to experimental investigations
- Basic ability to work independently and manage one’s time.
- Basic knowledge of Python, and SQL.
- Basic knowledge of computer vision and generative models.
- Basic knowledge with data ETL workflows & pipelines.
- [New] Usage of LLM for data labeling related work.
Education/Experience:
- Associate's degree or equivalent training required in Computer Science, Electronic Engineering, Physics, Bioinformatics, or other STEM subjects.
- Prior industrial experience in software development and testing and / or research experience in human computer interaction are preferred.
Additional Requirements:
- Be onsite, in MPK, working with engineers
Pay range is $40 - $45 per hour with full benefits available, including paid time off, medical/dental/vision/life insurance, 401K, parental leave, and more. Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
THE PROMISES WE MAKE:
At Crystal Equation, we empower people and advance technology initiatives by building trust. Your recruiter will prep you for the interview, obtain feedback, guide you through any necessary paperwork and provide everything you need for a successful start. We will serve to empower you along the way and provide the path for your professional journey.
For more information regarding our Privacy Policy, please visit crystalequation.com/privacy.
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Ready to jumpstart your career in the vibrant heart of Menlo Park, California? Nestled in the bustling Silicon Valley, this dynamic region beckons with unparalleled growth opportunities and a thriving tech-centric environment. Unleash your potential in the epicenter of innovation, where companies like Facebook and Stanford University drive groundbreaking advancements. With the picturesque Stanford University, the iconic Menlo Park Caltrain station, and the bustling downtown area brimming with cafes and boutiques, this locale offers a blend of charm and modernity like no other. Explore career opportunities surrounded by the lush landscapes of nearby parks like Bedwell Bayfront Park or catch a game at the Stanford Stadium. Join us in discovering the endless possibilities that await in Menlo Park and unlock your career aspirations today!