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Weekend Ai Data Annotation Jobs in California (NOW HIRING)

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... building data annotation and dataset management tools. Company : Figure is an AI robotics company that develops autonomous general-purpose humanoid robots. Founded in 2022, the company is ...

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... building data annotation and dataset management tools. Company : Figure is an AI robotics company that develops autonomous general-purpose humanoid robots. Founded in 2022, the company is ...

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... building data annotation and dataset management tools. Company : Figure is an AI robotics company that develops autonomous general-purpose humanoid robots. Founded in 2022, the company is ...

Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is ... Experience building data annotation and dataset management tools. The US base salary range for this ...

AI Data Platform Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Build AI-ready datasets through ground truth creation, data curation, annotation workflows, dataset versioning, and metadata management. Develop data quality frameworks, validation pipelines ...

Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is ... Experience building data annotation and dataset management tools. The US base salary range for this ...

Build AI-ready datasets through ground truth creation, data curation, annotation workflows, dataset versioning, and metadata management. Develop data quality frameworks, validation pipelines ...

Showing results 21-40

Weekend Ai Data Annotation information

What is a Weekend AI Data Annotation specialist?

Weekend AI Data Annotators are professionals who label, categorize, and tag data—such as images, audio, or text—for use in training artificial intelligence models, specifically working on weekends. Their work ensures that machine learning algorithms receive high-quality, accurately labeled datasets for tasks like computer vision, natural language processing, or speech recognition. This role often involves using specialized annotation tools and following precise guidelines to maintain consistency and accuracy. Weekend annotators may work remotely or on-site, and their contributions are vital for improving AI system performance.

What are common challenges faced by Weekend AI Data Annotation specialists, and how can they be managed?

Weekend AI Data Annotation specialists often encounter challenges such as maintaining high attention to detail during repetitive tasks and managing productivity over long annotation sessions. Since the work is typically remote or semi-remote, self-motivation and effective time management are crucial to meet project deadlines. It's helpful to take regular breaks, communicate proactively with team leads when questions arise, and make use of any annotation guidelines or quality assurance feedback provided. Collaborating with teammates through chat platforms or project management tools can also enhance consistency and resolve uncertainties quickly.

How much do you get paid for AI data annotation?

The pay for AI data annotation jobs varies depending on the employer, project complexity, and experience level, but typically ranges from $10 to $20 per hour or $0.02 to $0.10 per task. Many roles are paid on a per-task basis, and some may offer bonuses for accuracy or speed. Compensation can also depend on whether the work is freelance or employed by a company.

What skills and qualifications are needed to thrive as a Weekend AI Data Annotation specialist?

To thrive as a Weekend AI Data Annotation Specialist, you need attention to detail, strong analytical skills, and familiarity with data labeling processes, often supported by a high school diploma or post-secondary coursework in a technical field. Proficiency with annotation platforms like Labelbox, Supervisely, or internal company tools is typically required, along with basic knowledge of data privacy protocols. Reliability, time management, and effective communication are crucial soft skills for meeting project deadlines and collaborating with remote teams. These skills and qualities ensure the accuracy and efficiency of annotated datasets, which are essential for high-performing AI systems.
What are the most commonly searched types of Ai Data Annotation jobs in California? The most popular types of Ai Data Annotation jobs in California are:
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What cities in California are hiring for Weekend Ai Data Annotation jobs? Cities in California with the most Weekend Ai Data Annotation job openings:
Infographic showing various Weekend Ai Data Annotation job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Human Data Operations Strategist

Encord

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 21 days ago


Job description

About us

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.

 

Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.

 

The role

As a Human Data Operations Strategist, you will play a critical role in managing and optimising data annotation and machine learning workflows for our clients. You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models.

What you'll do

  • Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams

  • Ensure the highest standards of data quality by designing and refining annotation processes, auditing results, and implementing feedback loops

  • Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process

  • Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices

  • Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies

Who we're looking for

  • A sharp, execution-oriented operator with a consulting or AI company pedigree — you bring structured thinking, strong project management instincts, and a bias for getting things done

  • Analytically rigorous and comfortable with ambiguity — you break down complex operational challenges from first principles and build clear, actionable plans to solve them

  • Technically fluent enough to get hands-on with data — whether that's querying a database, auditing annotation outputs, or automating a workflow in Python

  • Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance

  • A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track

  • Entrepreneurial and collaborative — you thrive in fast-paced environments and take ownership without waiting to be told what to do

Experience requirements

  • 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies

  • Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration

  • Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued

  • Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks

  • Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions

  • Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams

Why Encord

  • Competitive salary, commission, and meaningful equity in a high-growth start-up

  • Clear, accelerated growth opportunities as the company scales rapidly

  • Strong in-person culture: 4 days/week

  • Flexible PTO to fully recharge

  • Annual learning & development budget

  • Comprehensive health, dental, and vision coverage

  • Frequent travel opportunities across the U.S., London, and Europe

  • Bi-annual company offsites, twice-weekly team lunches, and monthly socials