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Seasonal Remote Data Annotation Jobs in California

Corvus Robotics

Sr. ML Ops Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

We believe that data-driven, safe inventory management will optimize the global physical economy ... Experience setting up annotation tooling and workflows * Background in robotics autonomy and ...

LatchBio

AI Biologist - Biosurveillance

San Francisco, CA · On-site +1

$120K - $180K/yr

Bioinformatics Engineer - Biosurveillance As molecular data generation and frontier model ... Viral genome reconstruction, annotation, consensus generation, lineage or subtype assignment, and ...

Yardzen

Partnership Operations Coordinator

Mill Valley, CA · Remote

  • Medical

  • Dental

  • Vision

We're transforming the $200 billion outdoor renovation industry with AI, data, and technology ... Coordinate partner promotions, seasonal campaigns, discount codes, and merchandising opportunities.

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All JobsData Annotation JobsSeasonal Remote Data Annotation JobsSeasonal Remote Data Annotation Jobs in California

Seasonal Remote Data Annotation information

What is a seasonal remote data annotation job?

Seasonal remote data annotation jobs involve labeling and categorizing data—such as images, text, or audio—from home during busy periods when companies need extra help. These positions are typically temporary and align with peak business seasons or special projects. Data annotation is essential for training artificial intelligence and machine learning models to accurately interpret information. Working remotely in this role allows for flexible hours and the ability to contribute from anywhere with a reliable internet connection.

What are the key skills and qualifications needed to thrive as a seasonal remote data annotation specialist?

To thrive as a Seasonal Remote Data Annotation Specialist, you need strong attention to detail, basic computer literacy, and the ability to follow complex guidelines, typically supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and sometimes specialized software like image or text tagging systems is often required. Excellent time management, self-motivation, and clear written communication are critical soft skills for remote work success. These abilities ensure high-quality, accurate data output that supports machine learning projects and meets project deadlines.

What are some common challenges faced in a seasonal remote data annotation role, and how can they be managed?

Seasonal remote data annotation roles often require adapting quickly to fluctuating workloads and new annotation guidelines as projects change. Job seekers may find it challenging to maintain consistent accuracy and productivity while working independently from home, especially when handling repetitive tasks. To manage these challenges, it's helpful to establish a structured daily routine, stay updated on project instructions, and actively communicate with team leads or fellow annotators for clarification. Additionally, utilizing project management tools and regularly reviewing feedback can help maintain high-quality output throughout the season.

What is the difference between Seasonal Remote Data Annotation vs Data Labeling Specialist?

AspectSeasonal Remote Data AnnotationData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with familiarity in labeling tools
Work EnvironmentRemote, project-based, seasonalRemote or on-site, ongoing or project-based
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, computer vision
Search IntentSeasonal remote data annotation jobsData labeling jobs

Seasonal Remote Data Annotation involves short-term, project-based tasks focused on annotating data for AI models, often during peak seasons. Data Labeling Specialists may work year-round, providing ongoing data annotation services. While both roles require similar skills and tools, Seasonal Remote Data Annotation is typically temporary and tied to specific projects, whereas Data Labeling Specialists may have more continuous responsibilities.

What are the most commonly searched types of Seasonal Data Annotation jobs in California?

The most popular types of Seasonal Data Annotation jobs in California are:

What are popular job titles related to Seasonal Remote Data Annotation jobs in California?

For Seasonal Remote Data Annotation jobs in California, the most frequently searched job titles are:

What job categories do people searching Seasonal Remote Data Annotation jobs in California look for?

The top searched job categories for Seasonal Remote Data Annotation jobs in California are:

What cities in California are hiring for Seasonal Remote Data Annotation jobs?

Cities in California with the most Seasonal Remote Data Annotation job openings:

Seasonal Remote Data Annotation jobs near you
Infographic showing various Seasonal Remote Data Annotation job openings in California as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% Remote job distribution.

Sr. ML Ops Engineer

Corvus Robotics

Mountain View, CA • On-site, Remote

$123K - $169K/yr

Full-time

Re-posted 4 days ago

Job description

About Corvus
Every physical good spends time in a warehouse, and every warehouse tracks their inventory. Today, nearly 100% of warehouses track their inventory manually using barcode scanners and climbing forklifts.
We're Corvus Robotics. Our fully autonomous Corvus One™ drones use computer vision & robotics to automatically track inventory, improving worker safety and increasing labor efficiency. We believe that data-driven, safe inventory management will optimize the global physical economy and improve economic prosperity for humanity.
About the Role
With a growing fleet of autonomous drones and an expanding customer base, we're now ready to multiply ML iteration speed and unblock more advanced ML product delivery.
We're hiring a systems-oriented Senior Software Engineer to build the data infrastructure, training pipelines, and internal tooling that our ML team needs to move faster.
Specifically in this role you will:
  • Build and maintain the data pipeline infrastructure that consolidates internal infra, labeling tools, S3, and other data sources into a unified, queryable system
  • Build tooling for dataset selection and curation that can programmatically target specific data (by environment, object type, etc.)
  • Own ML data infra from robot to training run, accessible to the ML team without backend engineering help
  • Build model evaluation and regression testing infrastructure -- real metrics, not vibes or "someone complained in prod"
  • Automate the model retuning loop for standard tasks so ML engineers can be mostly hands-off on routine updates

This is a hybrid or remote role with periodic trips to HQ in Mountain View, CA.
Must Haves
  • 2-3 years shipping real production ML infrastructure for big datasets, not just scripts
  • Experience building distributed data pipelines that consolidate multiple sources
  • Demonstrated understanding of data flow from raw collection, labeled training set, to trained models
  • Experience building systems from scratch, or contributed heavily to a small-team infra build where the playbook didn't exist
  • Ability to thrive in a startup environment with high ambiguity. You'll figure out what to build

Nice to Haves
  • Experience setting up annotation tooling and workflows
  • Background in robotics autonomy and computer vision

Experience integrating with tools like Kubeflow, SLURM, or similar for scalable training workflows

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