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Overnight Ai Data Rater Jobs in Utah (NOW HIRING)

3M HEALTHCARE

Senior Data Scientist

Lehi, UT · On-site

$107K - $183K/yr

Senior Data Scientist - Overview nCino's Data & AI team is seeking a Senior Data Scientist to build intelligent automation and insights for our global cloud banking platform. The role collaborates

BambooHR

Distinguished Architect, Data Technology

Draper, UT · Hybrid

$59.50 - $76.75/hr

Please Note: This is a Utah-based hybrid position which will require some regular in-office days each week. Additionally, employment with BambooHR is contingent on passing both a background and

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Overnight Ai Data Rater information

What is an Overnight AI Data Rater?

Overnight AI Data Raters are individuals who work outside of regular business hours to evaluate and label data used to train artificial intelligence systems. Their main responsibilities include reviewing text, images, audio, or video content and providing accurate assessments or categorizations according to specific guidelines. This work is crucial in ensuring AI models can learn from high-quality and unbiased data. Typically, these roles are remote and may require attention to detail, consistency, and adherence to data privacy standards.

What are the key skills and qualifications needed to thrive as an Overnight AI Data Rater?

To thrive as an Overnight AI Data Rater, you need strong analytical skills, attention to detail, and proficiency in following complex guidelines, usually supported by at least a high school diploma or equivalent. Familiarity with data labeling tools, web browsers, and sometimes proprietary platforms is important, as well as the ability to quickly adapt to evolving AI systems. Excellent time management, self-motivation, and clear written communication help individuals excel in this often-remote, independent role. These skills ensure accurate data evaluation, which is crucial for improving AI systems and maintaining quality standards during off-peak hours.

What are some common challenges faced by Overnight AI Data Raters, and how can they be managed?

Overnight AI Data Raters often encounter challenges such as maintaining focus during late-night shifts and accurately evaluating large volumes of data within tight deadlines. Managing these challenges involves establishing a consistent sleep schedule, taking regular breaks to avoid fatigue, and using productivity tools to track progress. Collaborating with team members via chat platforms can also help resolve uncertainties in data interpretation, ensuring high-quality work even during less supervised hours.

What is the difference between Overnight Ai Data Rater vs Data Annotator?

AspectOvernight Ai Data RaterData Annotator
CredentialsBasic computer skills, sometimes high school diplomaBasic computer skills, sometimes high school diploma
Work EnvironmentRemote, flexible hours, often overnight shiftsRemote or on-site, flexible or regular hours
Industry UsageAI training data, machine learning modelsData labeling, training datasets for AI
Job FocusReviewing and rating data for AI modelsLabeling and annotating data for AI training

Both Overnight Ai Data Raters and Data Annotators work in AI data preparation, often remotely, with similar entry-level requirements. The key difference is that Overnight Ai Data Raters primarily review and rate data, often during overnight shifts, while Data Annotators focus on labeling and annotating data to create training datasets. Understanding these distinctions helps job seekers find roles aligned with their skills and preferred work hours.

What are the most commonly searched types of Ai Data Rater jobs in Utah?

The most popular types of Ai Data Rater jobs in Utah are:

What cities in Utah are hiring for Overnight Ai Data Rater jobs?

Cities in Utah with the most Overnight Ai Data Rater job openings:

Overnight Ai Data Rater jobs near you
Infographic showing various Overnight Ai Data Rater job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Sr. Director, Design Quality & Reliability - OCI Data Center Infrastructure

Salt Lake City, UT • On-site

Ll Oefentherapie
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Job description

Key Responsibilities Build and Lead the Function
  • Establish and scale OCI’s Design Quality & Reliability organization for AI data centre infrastructure.
  • Develop the strategy, operating model, governance, metrics, and execution roadmap for the function.
  • Build and lead a high-performing multidisciplinary team spanning reliability engineering, supplier quality, design assurance and validation,
  • Define organisational processes and standards for quality and reliability across the infrastructure lifecycle.
Design Quality & Reliability Leadership
  • Ensure infrastructure designs meet OCI reliability, resiliency, maintainability, and lifecycle performance requirements.
  • Drive design assurance processes that validate design intent against operational requirements and long-term reliability objectives.
  • Lead cross-functional design reviews focused on reliability risk reduction, failure prevention.
  • Establish reliability engineering methodologies including FMEA, fault tree analysis, accelerated life testing, and design-for-reliability practices.
Product Quality & Supplier Reliability
  • Define qualification and acceptance criteria for critical infrastructure products and systems used in OCI data centres.
  • Establish product quality benchmarks and reliability performance targets, including AFR (Annualised Failure Rate), IDR, MTBF, and other key reliability indicators.
  • Develop supplier quality management frameworks and collaborate with strategic suppliers to improve product reliability and manufacturing quality.
  • Support root cause analysis and corrective action processes for field failures and reliability excursions.
Metrics, Benchmarking & Continuous Improvement
  • Develop KPI dashboards and measurement systems to benchmark design and product reliability performance across the OCI infrastructure portfolio.
  • Analyse field performance data, warranty trends, operational incidents, and failure modes to identify systemic improvement opportunities.
  • Establish data-driven processes to recommend and implement design, component, or supplier changes that improve quality, reliability, and operational efficiency.
  • Benchmark OCI performance against hyperscale and industry best practices.
Cross-Functional Partnership
  • Partner with Infrastructure Capacity Delivery, Operations, Supply Chain, and Product teams to ensure reliability objectives are embedded throughout the lifecycle.
  • Influence strategic technology and supplier selection decisions using quality and reliability data.
  • Provide executive-level reporting on reliability performance, risks, and improvement initiatives.
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