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Labeling Jobs in California (NOW HIRING)

Label, ink stamp, overcoat and etch outlined information on detail components and assemblies using general shop tools and equipment. What will my responsibilities include? * Perform label, ink stamp ...

Label Operator

Oceanside, CA · On-site

$17 - $18/hr

Label, ink stamp, overcoat and etch outlined information on detail components and assemblies using general shop tools and equipment. What will my responsibilities include? * Perform label, ink stamp ...

Showing results 41-60

Labeling information

See California salary details

$10

$13

$16

How much do labeling jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for labeling in California is $13.78, according to ZipRecruiter salary data. Most workers in this role earn between $12.36 and $15.19 per hour, depending on experience, location, and employer.

What is the difference between Labeling vs Packaging Worker?

AspectLabelingPackaging Worker
Primary RoleApplying labels to products or packagingAssembling, packing, and preparing products for shipment
Skills & CertificationsAttention to detail, basic labeling equipment knowledgePhysical stamina, ability to operate packing machinery
Work EnvironmentManufacturing or warehouse settingsWarehouse, distribution centers, manufacturing plants
Industry UsageCommon in food, pharmaceuticals, consumer goodsCommon in logistics, retail, manufacturing

Labeling involves applying labels to products or packaging, focusing on accuracy and detail. Packaging workers handle the assembly and packing of products for shipment, requiring physical stamina and operational skills. While both roles are essential in manufacturing and warehouse environments, labeling emphasizes precision in labeling tasks, whereas packaging focuses on product assembly and readiness for distribution.

What kind of education is needed for labeling?

Labeling jobs typically require a high school diploma or equivalent. Basic skills in reading, attention to detail, and familiarity with tools or equipment used in labeling are important; additional training or on-the-job instruction is common. Formal certifications are generally not required but can be beneficial for advancement.

What are some common challenges faced by professionals in labeling roles, and how can they be addressed?

Professionals in labeling roles often encounter challenges such as maintaining high levels of accuracy and consistency when reviewing large volumes of data. Time management can also be demanding, as deadlines may be tight and tasks repetitive. To address these challenges, it's helpful to develop strong attention to detail, utilize quality assurance tools, and communicate proactively with team members to resolve uncertainties. Many teams also implement regular feedback sessions and clear guidelines to ensure consistency across projects.

What are the key skills and qualifications needed to thrive as a labeling specialist, and why are they important?

To thrive as a Labeling Specialist, you need strong attention to detail, knowledge of regulatory requirements, and experience with documentation management, often supported by a background in life sciences or a related field. Familiarity with labeling software, regulatory databases, and industry standards such as FDA or EMA guidelines is typically required. Excellent organizational skills, clear communication, and the ability to collaborate across departments help set top performers apart. These skills are essential to ensure labeling accuracy, regulatory compliance, and timely product approvals in highly regulated industries.

What is a labeling job?

Labeling jobs involve identifying, tagging, or categorizing data, such as images, text, audio, or video, to help train machine learning models. These roles are crucial in preparing high-quality datasets for artificial intelligence systems, ensuring that the data is accurately annotated and easy for algorithms to understand. Labelers may work with specialized software to mark up objects, transcribe information, or classify content according to specific guidelines. This work is often done remotely and can range from simple tasks to more complex annotation requiring domain expertise.

What are the most commonly searched types of Labeling jobs in California?

The most popular types of Labeling jobs in California are:

What are popular job titles related to Labeling jobs in California?

For Labeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Labeling jobs in California look for?

The top searched job categories for Labeling jobs in California are:

What cities in California are hiring for Labeling jobs?

Cities in California with the most Labeling job openings:

Infographic showing various Labeling job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 17% Part Time, 2% Temporary, 3% Contract, and 2% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $28,672 per year, or $13.8 per hour.

Staff ML Engineer, Perception: Auto-labeling

Rivian

Palo Alto, CA • On-site

$228K - $285K/yr

Full-time

Medical, Dental, Vision

Re-posted yesterday


Rivian rating

7.3

Company rating: 7.3 out of 10

Based on 159 frontline employees who took The Breakroom Quiz

20th of 44 rated automakers


Job description

About Rivian
Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what's possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Role Summary
Auto-labelling is a foundational pillar of the Autonomy stack. In this Staff ML Engineer role, you will play a key role in driving and delivering high-quality, scalable auto-labeling models. This includes training, optimizing and shipping auto-labeling models in the Autonomy stack. Use cases include mapping, lanes auto-labelling, object auto-labelling as well as other critical applications. You will ship production-grade models that push the boundaries of what's possible. As such, you will also drive the whole end-to-end ML lifecycle & data flywheel of this effort: data acquisition, metrics definition, evaluation, model performance optimization, feedback loop. A key part of the role is especially dedicated to lidar-free auto-labeling, i.e. ship auto-labeling models that do not require lidar data.
Responsibilities
  • Drive and deliver prod-grade, high-quality, scalable auto-labeling models. Use cases include AV mapping, lanes auto-labelling and/or object auto-labelling, among other critical applications.
  • Push the performance of lidar-free auto-labeling.
  • Establish rigorous evaluation and monitoring benchmarks. Identify and root-cause top-tier system anomalies, prioritizing high-impact optimizations to continuously push the needle on performance.
  • Partner closely with the Autonomy group to ensure we meet the feature requirements
  • Collaborate across teams to define target requirements and guide technical trade-off decisions.

Qualifications
  • Education: BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a highly related quantitative field.
  • Experience: 7+ years of professional experience scaling ML solutions, with a strong focus on the following
    • AV auto-labeling system at scale: Proven track record of hands-on experience driving and delivering auto-labeling models for Autonomous Vehicles at scale. Auto labeling for mapping, lanes auto-labelling and/or object auto-labelling.
    • Perception stack: solid understanding of the AV perception stack.
    • System engineering: Strong proficiency in Python alongside a solid understanding of modern Perception pipelines, benchmarking tools, and infrastructure.
    • Execution: Demonstrated ability to drive progress across a complex system spanning multiple domains and components, in a fast-paced environment.

Preferred Qualifications
  • Experience in Lidar-free auto-labeling
  • Experience in mapping, especially from multiple vehicle passes and/or lidar-free mapping.
  • Experience in defining data annotation guidelines and partnering effectively with in-house and external 3P annotation vendors.
  • Experience in complex,multi-modal, large-scale data flywheel
  • Experience with multiple modalities (e.g., cameras, LiDAR, Radar).
  • Experience with onboard edge deployment, cloud inference architectures, and balancing compute/efficiency trade-offs

Pay Disclosure
Salary Range for California Based Applicants: $228,000 - $285,000 (actual compensation will be determined based on experience, location, and other factors permitted by law).
Benefits Summary: Rivian provides robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26. Coverage is effective on the first day of employment, and Rivian covers most of the premium
Equal Opportunity
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com.
Candidate Data Privacy and Technology
Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes ("Candidate Personal Data"). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.
Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian's service providers, including providers of background checks, staffing services, and cloud services.
Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.
How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.
AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate.
Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way.
Please note that we are currently not accepting applications from third party application services.

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About Rivian

Sourced by ZipRecruiter

Rivian is a pioneering automotive industry player headquartered in Irvine, California. Established in 2009, the company has made notable advancements in developing sustainable transportation solutions. It is widely recognized for its electric adventure vehicles: the R1T pickup and the R1S SUV. Rivian is dedicated to creating a positive shift in societal mobility and emphasizes sustainability, innovation, and adventure as part of its core values. Their mission is to keep the world adventurous forever - a testament to their commitment in transitioning the world to sustainable transportation. Rivian's achievements are numerous, with one of the most notable being securing a significant multi-billion dollar investment from Amazon for the production of electric delivery vans.

Industry

Automobile dealers

Company size

10,000+ Employees

Headquarters location

Irvine, CA, US

Year founded

2009