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Overnight Ai Data Rater Jobs in California (NOW HIRING)

C3 AI

Data Scientist/Senior Data Scientist

Redwood City, CA · On-site

$136K - $183K/yr

... AI Platform. * Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements. * Collaborate with data ...

C3 AI

Data Scientist/Senior Data Scientist

Redwood City, CA · On-site

$136K - $183K/yr

... AI Platform. * Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements. * Collaborate with data ...

Maxinsights

Data Partnership Manager

Santa Clara, CA · On-site

... AI model training. If you are deeply interested in building a "data production network" and are ... rates, etc.) to continuously optimize operational efficiency. Collaborate with the Business ...

Meta

Product Data Operations Program Manager

Menlo Park, CA · On-site

$103K - $155K/yr

Meta is seeking a Product Data Operations Program Manager to drive AI solutions and data programs ... quality rates, and delivery timelines - to stakeholders at varying leadership levels • Provide ...

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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 California?

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

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

Cities in California 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 California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

AI Data Engineer - Scientific Data Platforms (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$35 - $38/hr

Full-time

Re-posted 6 days ago

Job description

Pay Rate Low: 35 | Pay Rate High: 40
Our client is a leading global biotechnology and pharmaceutical organization driven by a mission to innovate, continuously advance science, and ensure everyone has access to the healthcare they need.
Title: AI Data Engineer - Scientific Data Platforms
Location: Remote, Must work PST
Pay rate: $35-38/hr (Depends on experience level)
Schedule: Full-time (40 hours/week)
Duration: 1-year contract, (Plus benefits)
Position Overview
This role addresses a critical need in scaling our AI models for drug discovery by building largely automated, scalable, agent-driven data ingestion and curation pipelines for genomics data. This includes metadata inference, constructing performant query architectures, and transforming high-dimensional datasets (e.g., single-cell omics, clinical trials) into AI-ready training formats.
Key Responsibilities
  • Build an agentic data ingestion pipeline and move beyond bespoke steps toward agents that teams can reliably use as a shared, deployed service.
  • Triage and prioritize incoming requests to ingest specific datasets. Clean and organize data, building the first-pass cleaning and organization steps into the agentic flow.
  • Validate cross-modal linkage. Add automated checks that catch when ingested data does not connect correctly and flag low-quality or mismatched records.
  • Version every dataset, retaining and making prior versions addressable. Preserve raw data and provenance, ensuring agent workflows log validation and transformation steps so lineage is fully traceable.
  • Partner with AI, software engineering, and computational biology groups to co-define data standards and conventions.

Qualifications & Requirements
  • Demonstrated experience building multi-agent workflows or LLM workflows using tools/frameworks such as LangGraph or LlamaIndex, including tool/function calling and asynchronous task execution.
  • Strong Python skills for data manipulation, working with APIs and databases, and handling heterogeneous data formats.
  • Familiarity with dataset versioning approaches (e.g., DVC, lakeFS, or equivalent).
  • Comfortable with or showing a strong willingness to learn common omics data formats like AnnData, H5AD, and TileDB.
  • No deep bioinformatics expertise required; just a basic conceptual understanding of different modalities (e.g., RNA-seq vs. scRNA-seq vs. WES; genomics vs. transcriptomics vs. proteomics vs. metabolomics).
  • Comfortable writing unit and functional tests to ensure data processing workflows are reliable and reproducible.
  • Degree in a technical field or equivalent practical experience.
  • Must be Authorized to work in the United States without Sponsorship.
Nice to Have
  • Experience deploying agent workflows as a shared service (e.g., FastAPI or MCP endpoints).
  • Exposure to cloud platforms (AWS, GCP) and containerization (Docker).
  • Familiarity with scientific workflow managers such as Nextflow or Snakemake.

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