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Video Annotation Jobs in California (NOW HIRING)

Sieve is an AI research lab focused on video data, aiming to solve the bottleneck in the growth of ... data annotation, curation, and quality review • Build and improve QA processes to ensure data ...

Responsibilities : • Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots • Collaborate with ML engineers to refine ...

... audio, video, and 3D data. • Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model ...

... audio, video, and 3D data. • Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model ...

Preferred : • Experience with video understanding (temporal consistency, tracking, video segmentation) • Experience with foundation models for data annotation • Experience with MLOps tooling ...

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in ... Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines ...

Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots * Collaborate with ML engineers to refine labeling guidelines and ...

Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots * Collaborate with ML engineers to refine labeling guidelines and ...

This position involves using proprietary annotation tools to label objects, poses, and interactions in images and video streams from humanoid robots. You will play a key role in maintaining high ...

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Preferred : • Experience with multimodal datasets (text, image, video, audio, or 3D). • Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Preferred : • Experience with multimodal datasets (text, image, video, audio, or 3D). • Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

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Video Annotation information

What is a Video Annotation job?

A Video Annotation job involves labeling objects, activities, or events within videos to help train machine learning models. Annotators use specialized tools to draw bounding boxes, segment frames, or classify scenes to improve AI's ability to recognize visuals. This work is essential for applications like autonomous vehicles, facial recognition, and action recognition in AI systems.

What are the typical daily responsibilities of a Video Annotation specialist?

As a Video Annotation specialist, your daily tasks will generally involve watching video footage, identifying relevant objects or actions, and accurately labeling or tagging frames according to specific project guidelines. You may also review and validate annotations to ensure quality and consistency, collaborate with team members or project managers to clarify labeling instructions, and document any ambiguities or challenges encountered during annotation. Most roles are structured with clear targets or quotas for completed work, and you may work independently or as part of a larger team supporting AI development projects. The position requires strong concentration and the ability to handle repetitive tasks efficiently while maintaining high standards of accuracy.

What are the key skills and qualifications needed to thrive in the Video Annotation position, and why are they important?

To excel in Video Annotation, you need strong attention to detail, visual analysis skills, and familiarity with video processing concepts, often supported by a diploma or coursework in computer science or a related field. Knowledge of annotation tools such as CVAT, Labelbox, or VGG Image Annotator, and, in some cases, experience with basic scripting or data management platforms, is highly valued. Excellent focus, time management, and the ability to follow precise instructions help individuals stand out in this position. These abilities are crucial for ensuring the accuracy and quality of annotated video data, which directly impacts AI and machine learning model performance.

What are the most commonly searched types of Video Annotation jobs in California? The most popular types of Video Annotation jobs in California are:
What are popular job titles related to Video Annotation jobs in California? For Video Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Video Annotation jobs in California look for? The top searched job categories for Video Annotation jobs in California are:
What cities in California are hiring for Video Annotation jobs? Cities in California with the most Video Annotation job openings:
Infographic showing various Video Annotation job openings in California as of July 2026, with employment types broken down into 1% As Needed, 49% Full Time, 44% Part Time, 3% Contract, and 3% Nights. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.
Driving Scenario Specialist

Driving Scenario Specialist

PROLIM Global Corporation

Foster City, CA • On-site

Full-time

Posted 10 days ago


Job description

Job Title: Driving Scenario Specialist
Location: Foster City, California
Job Overview:
We are looking for a Driving Scenario Specialist to join a cutting-edge autonomous vehicle program. This role involves analyzing complex driving data and supporting AI/ML model improvement for real-world driving scenarios.
Key Responsibilities:
  • Perform high-level scenario analysis using video, LiDAR, and sensor data
  • Evaluate actor behavior, environmental risks, and driving patterns
  • Identify and document edge cases and anomalies
  • Collaborate with engineering and AI teams to improve annotation guidelines
  • Create detailed documentation and scenario reports
  • Ensure data quality, validation, and dataset accuracy
  • Participate in calibration sessions with technical teams
Required Skills:
  • Experience in Automotive / OEM domain
  • Knowledge of ADAS / Autonomous Driving systems
  • Strong understanding of sensor data (LiDAR, camera, logs)
  • Experience in scenario analysis, annotation, or validation
  • Strong analytical and documentation skills
  • Experience with data tools, spreadsheets, or AI tools
Qualifications:
  • B.E / B.Tech in Engineering (Mandatory)