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Annotation Labelling Jobs in Santa Clara, CA (NOW HIRING)

iMerit

Be Seen First

Video Data Annotator

San Jose, CA · Remote

$35/hr

Identify and label specific actions, objects, or events within video data, ensuring comprehensive and precise annotation. * Collaborate with the iMerit project team to clarify annotation standards ...

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

Strong understanding of ML development workflows, data pipelines, and annotation lifecycle. * Experience managing large-scale data labeling or data collection efforts, including working with third ...

General Motors

Senior ML Systems Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops), helping us move from human-only to ...

SpaceXAI

Human Data - Engineer

Palo Alto, CA · On-site

$144K - $270K/yr

Design and improve annotation workflows, labeling interfaces, and related tools with a focus on data quality and integrity. * Act as a liaison between engineering, technical staff, and tutoring ...

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Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an annotation labelling specialist?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by annotation labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Santa Clara, CA?

For Annotation Labelling jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Annotation Labelling jobs in Santa Clara, CA look for?

The top searched job categories for Annotation Labelling jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Annotation Labelling jobs?

Cities near Santa Clara, CA with the most Annotation Labelling job openings:

Annotation Labelling jobs near you

Senior Manager, Product - Perception Data

Nvidia

Santa Clara, CA • On-site

$148K - $196K/yr

Full-time

Re-posted 14 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

NVIDIA is developing AI and Accelerated Computing solutions for the Automotive industry. We are looking for a Senior Manager of Product to join our data team and lead a product group. Your core mission is to deeply understand what perception models need to improve - and translate that understanding into high-quality, high-value data annotation strategies that directly drive model performance gains.

This role sits at the intersection of perception research, data engineering, and labeling operations. You will work closely with perception scientists to identify model performance gaps, define annotation requirements, own the data roadmap, and drive end-to-end delivery across labeling vendors and internal teams. The best candidate combines strong product instincts with genuine technical depth in ML data pipelines and perception tasks.

What You'll Be Doing:

  • Develop a deep understanding of how training data impacts perception model performance across tasks including 3D object detection, lane/road structure recognition, traffic sign and traffic light detection, and semantic segmentation.

  • Partner with perception researchers and engineers to translate model capability gaps into concrete data requirements.

  • Own annotation ontology design: define labeling taxonomies, attribute schemas, edge case handling rules, and inter-annotator consistency standards for perception network tasks such as 3D bounding boxes, lane elements, traffic sign/light classification and association.

  • Anticipate how changes in data density, ROI size, and label complexity affect labeling throughput and delivery capacity; provide data-backed forecasts to stakeholders.

  • Collaborate with global engineering and labeling teams to ensure data quality and explore how DNN/LLM/VLM improves the performance of data labeling.

What We Need to See:

  • BS degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience).

  • 8+ years of product management experience, with at least 2+ years in a role directly involving ML/AI model development, data pipelines, or training data strategy.

  • Genuine understanding of perception model fundamentals.

  • Strong cross-functional communication skills.

  • 3+ years of experience leading or mentoring a team of product managers, tech leads, or equivalent.

Ways to Stand Out from the Crowd:

  • Fluent in Mandarin Chinese a strong plus (team operates across US and China time zones).

  • Direct experience in autonomous driving, robotics, or ADAS product development

  • Familiarity with 3D reconstruction, SLAM, NeRF, LiDAR point cloud annotation, and multi-sensor fusion.

  • Exposure to model-in-the-loop, human-in-the-loop, auto labeling, or VLM labeling.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forwardthinking and hardworking people in the world working for us. If you're passionate about AI, data, defining what the model can and cannot learn, and enabling worldclass AI models with highquality data, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 25, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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