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Part Time Ai Data Labeling Jobs in California (NOW HIRING)

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... Oversee cap table management and ensure data accuracy. * Ensure compliance with regulatory ...

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... Oversee cap table management and ensure data accuracy. * Ensure compliance with regulatory ...

Requirements: * Enrolled in an MS or PhD program pursuing a degree in Computer Science, Data ... Open to Remote Expected Contract Length: 12-months (this is a part -time role that is project based ...

Accountant (R5520)

San Diego, CA ยท On-site

$66K - $100K/yr

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... This role goes beyond the close, you will influence how financial data is produced, trusted, and ...

Electrical Engineer I (SD)

San Diego, CA ยท On-site

$81K - $122K/yr

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... Military fellows and part-time employees are not eligible for benefits. Please speak to your talent ...

Electrical Engineer I (SD)

San Diego, CA ยท On-site

$81K - $122K/yr

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... Military fellows and part-time employees are not eligible for benefits. Please speak to your talent ...

Electrical Engineer I (SD)

San Diego, CA ยท On-site

$81K - $122K/yr

Shield AI is a venture-backed defense-tech company with the mission of protecting service members ... Military fellows and part-time employees are not eligible for benefits. Please speak to your talent ...

Showing results 21-40

Part Time Ai Data Labeling information

What are the key skills and qualifications needed to thrive as a part time AI data labeling specialist?

To thrive as a Part Time AI Data Labeling Specialist, you need attention to detail, basic computer literacy, and often a high school diploma or equivalent. Familiarity with labeling platforms, annotation tools, and sometimes experience with data management systems is typically required. Reliability, time management, and the ability to follow precise instructions are crucial soft skills for this role. These skills ensure high-quality, accurate datasets that support effective machine learning model development.

What is part time AI data labeling?

Part-time AI data labeling involves annotating or categorizing data such as images, text, audio, or video to train and improve artificial intelligence and machine learning models. As a part-time data labeler, you work flexible hours to tag or classify data according to specific guidelines provided by a company or research team. This role is essential for creating high-quality datasets that help AI systems learn to recognize patterns, objects, or language. The work can often be done remotely and may require attention to detail and basic computer skills. Many companies hire part-time data labelers to handle large volumes of data efficiently.

What is the difference between Part Time Ai Data Labeling vs Part Time Data Annotation Specialist?

AspectPart Time Ai Data LabelingPart Time Data Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexible hoursRemote or onsite, flexible schedule
Industry UsageAI, machine learning, tech companiesData management, research, tech sectors
Job FocusLabeling data for AI trainingAnnotating data for various applications

Part Time Ai Data Labeling and Part Time Data Annotation Specialist roles share similar credentials and work environments, often involving remote work and flexible hours. The main difference lies in the specific focus: AI Data Labeling emphasizes preparing data for machine learning models, while Data Annotation Specialists may work on broader data types for various purposes. Both roles are essential in data-driven industries and often overlap in skills and industry usage.

What are some common challenges faced by part time AI data labelers, and how can they be effectively managed?

Part-time AI data labelers often encounter challenges such as repetitive tasks, maintaining high accuracy, and adapting to evolving labeling guidelines. To manage these, it's important to take regular breaks to prevent fatigue, stay updated on any changes to annotation protocols, and communicate with supervisors or team members when clarifications are needed. Leveraging available training resources and quality assurance feedback can also help improve performance and make the work more engaging. Collaboration with other labelers through team chats or forums can provide support and insights for handling tricky cases.
What are the most commonly searched types of Ai Data Labeling jobs in California? The most popular types of Ai Data Labeling jobs in California are:
What are popular job titles related to Part Time Ai Data Labeling jobs in California? For Part Time Ai Data Labeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Part Time Ai Data Labeling jobs in California look for? The top searched job categories for Part Time Ai Data Labeling jobs in California are:
What cities in California are hiring for Part Time Ai Data Labeling jobs? Cities in California with the most Part Time Ai Data Labeling job openings:
Infographic showing various Part Time Ai Data Labeling job openings in California as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Marketing Analytics & AI Automation Associate (Part-Time)

German International School of Silicon Valley

Mountain View, CA โ€ข On-site

$36 - $45/hr

Part-time

Posted 10 days ago


Job description

Marketing Analytics & AI Automation Associate (Part-Time)

GISSV is a K-12 German international school in Silicon Valley. Families choose us the way they choose a house: months of research, multiple campus visits, a five-figure annual decision, and a commitment that often lasts a decade. That makes our marketing funnel unusually long, unusually measurable, and unusually high-stakes. We're looking for someone analytical to build the measurement layer under it and to automate the repetitive parts of the work with AI agents. You'll work directly with our fractional CMO, who sets strategy; you own the technical execution.

There's a real number at the bottom of the funnel. Inquiry → tour → application → enrolled. Every conversion has a dollar value attached and a name behind it. You will be able to point at what you moved. You're the technical half of a  two-person team, not an extra pair of hands. We already have a strong marketing generalist covering brand, content, and stakeholder relationships. You're being hired for the complement: data, tooling, measurement, automation.

You'll be coached, not just supervised. Your manager is a fractional CMO. Standing weekly working sessions, direct feedback on your work, and a portfolio of real artifacts at the end — not a certificate of completion. We actually want you to use AI profoundly. If you've been building agentic workflows on your own time and looking for somewhere to point them at a real problem, this job is for you.

Essential Duties and Responsibilities:
  • Measurement foundation:
    • Audit and repair GA4, conversion tracking, and UTM discipline across all channels
    • Define the funnel stages and the events that mark them; make the definitions stick
    • Build a single recurring dashboard the leadership team and board will actually read
  • Consistent reporting cadence:
    • Weekly channel snapshot, monthly funnel review, term-based board reporting
    • Own the numbers end to end: pull, sanity-check, interpret, present
    • Flag what's off before anyone has to ask
  • Agentic workflow builds progressively, as the data foundation allows:
    • Competitive analysis — automated monitoring of peer and competitor schools: positioning, pricing, events, ad creative, organic presence
    • Audience segmentation — moving from one undifferentiated parent audience to defined segments with distinct motivations
    • Personalization — segment-appropriate messaging across email, landing pages, and paid
    • Signal-based journey measurement — identifying the behaviors that actually predict an application, and instrumenting for them
  • Other duties and/or projects as assigned.
Experience and Qualifications:
  • Currently enrolled (undergrad or grad) or recently graduated — Santa Clara, Stanford, Berkeley, or nearby
  • Genuine comfort with data: you can work in spreadsheets fluently, and SQL or Python is a strong plus
  • Hands-on experience building something with LLMs beyond chatting with one — automations, agents, scripts, scrapers, evals
  • Self-directing. Much of this is remote and asynchronous. We'll give you context and clear priorities; we can't give you constant supervision.
  • Available through at least June 2027

We are explicitly not requiring a marketing background. Some of the strongest candidates for this role will be studying data science, statistics, CS, symbolic systems, economics, or IEOR. If you can reason about numbers and build things, we'll teach you the marketing.

  • Nice to have:
    • German language ability
    • Familiarity with GA4, Google Ads, Meta Ads Manager, or a marketing automation platform
    • Any exposure to education, nonprofit, or another long-consideration-cycle purchase
 

FLSA Classification: Non-Exempt (hourly)

Hours: 20 hours/week, flexible around your class schedule

Reports To: Fractional CMO; works closely with the marketing generalist and the admissions team

Location: Remote-first; roughly two days per month on campus in Mountain View, plus a small number of admissions events

Pay Scale: $36.00 - $45.00 per hour worked, depending on experience

Please note that we are only able to accept applications of candidates who fulfill the language requirements and who are eligible to work in the US (sponsorship of work visa is not available for this position).

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