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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 ...

Insight Global

AI Robotics Data Collector

Los Angeles, CA · On-site

$30 - $33/hr

AI Data Creator Duration: 6 Month Contract to Hire Pay Rate: Up to $30/hour ($33/ hour for the overnight shift) Location(s)*: Los Angeles, CA 90016 *Santa Monica, Inglewood, North Hollywood and Santa ...

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Ai Data Rater information

What is an AI data rater?

An AI Data Rater evaluates and rates AI-generated content, such as search engine results, chat responses, or recommendations, to improve machine learning models. They follow specific guidelines to assess relevance, accuracy, and quality. This role helps refine AI systems by providing valuable feedback to enhance their performance. It typically requires strong analytical skills, attention to detail, and familiarity with the subject matter being rated.

What skills and qualifications are needed to thrive as an AI data rater?

To succeed as an AI Data Rater, you need strong analytical skills, attention to detail, and proficiency in evaluating data quality, typically requiring at least a high school diploma or equivalent. Familiarity with computer systems, web browsers, and proprietary rating platforms is often necessary, and training in data privacy or AI guidelines is sometimes provided. Excellent time management, adaptability, and effective written communication help candidates stand out in this largely remote and independent role. These skills ensure accurate data evaluations, support AI improvement, and enable consistent, high-quality performance.

What does an AI data rater do?

As an AI Data Rater, your main responsibilities include reviewing and evaluating various types of data—such as search queries, images, or social media content—according to detailed guidelines provided by your employer. You will typically work independently, using specialized tools or web-based platforms to rate data quality, relevance, or appropriateness. Attention to detail and consistency are important, as your feedback directly impacts the effectiveness of AI systems. Depending on the employer, you may also participate in training sessions or occasional team meetings to stay updated on the latest guidelines or project requirements.

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 are popular job titles related to Ai Data Rater jobs in California? For Ai Data Rater jobs in California, the most frequently searched job titles are:
What job categories do people searching Ai Data Rater jobs in California look for? The top searched job categories for Ai Data Rater jobs in California are:
What cities in California are hiring for Ai Data Rater jobs? Cities in California with the most Ai Data Rater job openings:
Ai Data Rater jobs near you
Infographic showing various Ai Data Rater job openings in California as of August 2026, with employment types broken down into 58% Full Time, and 42% Part Time. Highlights an 60% In-person, and 40% 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 22 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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