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Senior Video Annotation Jobs in California (NOW HIRING)

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Senior Video Annotation information

What is a senior video annotation?

A Senior Video Annotation specialist is a professional responsible for labeling, tagging, and categorizing objects or actions within video data, often for use in machine learning and artificial intelligence projects. They oversee and guide annotation teams, ensure high-quality data labeling, and help develop guidelines and best practices. Their expertise is crucial for training accurate computer vision models, as they provide the ground truth data that algorithms learn from.

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

To excel as a Senior Video Annotation Specialist, you need advanced skills in data labeling, attention to detail, and experience with video annotation tools, often supported by a degree in computer science or a related field. Familiarity with annotation platforms like CVAT, Labelbox, or VGG Image Annotator, and understanding of basic machine learning concepts, are typically required. Strong organizational skills, problem-solving abilities, and effective communication help ensure accuracy and seamless collaboration with data science teams. These competencies are vital for producing high-quality annotated datasets that drive the performance of computer vision models.

What are some common challenges faced by senior video annotation professionals, and how can they be addressed?

Senior Video Annotation professionals often encounter challenges such as maintaining consistency in labeling complex visual data, meeting tight project deadlines, and managing large volumes of video content. To address these issues, it's important to establish clear annotation guidelines, utilize efficient annotation tools, and foster open communication within the annotation team. Regular training and quality assurance checks can also help ensure high accuracy and efficiency, positioning team members for leadership and quality control roles as they advance.

What is the difference between Senior Video Annotation vs Video Labeler?

AspectSenior Video AnnotationVideo Labeler
Required CredentialsTypically requires experience in annotation tools, basic understanding of video content, and sometimes a degree in related fieldsUsually requires familiarity with labeling software and basic video content understanding, but less experience needed
Work EnvironmentOften part of a team working on complex projects, possibly remote or in-officeTypically focused on individual tasks, often remote, with repetitive labeling work
Employer & Industry UsageUsed in AI/ML companies, autonomous vehicle development, and tech firmsCommon in data annotation companies, AI startups, and research labs

Senior Video Annotation roles involve more complex tasks, oversight, and experience, while Video Labelers focus on basic labeling tasks. The senior role often requires a deeper understanding of video content and annotation tools, making it suitable for those with more experience. Both roles are essential in AI data preparation but differ in scope and responsibility.

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 Senior Video Annotation jobs in California?

For Senior Video Annotation jobs in California, the most frequently searched job titles are:

What job categories do people searching Senior Video Annotation jobs in California look for?

The top searched job categories for Senior Video Annotation jobs in California are:

What cities in California are hiring for Senior Video Annotation jobs?

Cities in California with the most Senior Video Annotation job openings:

Senior Machine Learning Data Engineer

Applied Intuition

Sunnyvale, CA โ€ข On-site

$150 - $240/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

About the role

The Axion Data team at Applied Intuition is building the data engine to train perception models. We build the means to run models at the edge such as Automatic Target Recognition (ATR) models, then backhaul data to our cloud pipeline that ingests and manages this data to enable the continual improvement of these models.

As a data engineer experienced in machine learning, you will be responsible for both our edge application which runs perception stacks and our cloud data engine which ingests video data to run the next iteration of the model before we deploy it back down to the edge. This includes optimizing our ability to run these models on both the edge and the cloud, as well as building MLOps tooling to gain insight and visibility into the pipeline for our stakeholders.

At Applied Intuition, you will:
  • Construct optimized data pipelines to run ML models

  • Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles

  • Integrate foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery

  • Leverage software-in-the-loop and hardware-in-the-loop testing

  • Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience

We're looking for someone who has:
  • 5+ years of relevant work experience

  • Familiarity with modern ML infrastructure, data-centric AI approaches and running large-scale jobs on GPUs

  • Created or worked on microservices and/or databases for data-oriented software

  • A hunger to learn and grow into a position of ownership and impact on a new product team

  • U.S. citizenship (legally required) and eligibility to obtain a security clearance

Nice to have:
  • Full-stack experience React, TypeScript Python, Golang or similar

  • Experience with Docker, Kubernetes, Opensearch and Postgres

  • Direct experience with foundation models, including LLMs and VLMs, for data automation tasks

  • Background in autonomous driving or robotics perception

  • Experience with active learning, auto-labeling, or human-in-the-loop ML systems

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job postingโ€™s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is:$150,000 - $240,000 USD annually.

Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. The laws require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.

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