1

Virtual Data Labelling Jobs (NOW HIRING)

Data Analyst

Foster City, CA · Remote

$85K - $100K/yr

We run these virtual- and private-label marketplaces in one of the nation's largest media networks ... You will be required to develop a deep understanding of the related data sources and leverage them ...

You will own the expert-labelled data and adjudication that trains, evaluates, and calibrates these ... Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual ...

Senior Data Analyst

Foster City, CA · Remote

$80K - $130K/yr

We run these virtual- and private-label marketplaces in one of the nation's largest media networks ... You will be required to develop a deep understanding of the related data sources and leverage them ...

Showing results 41-60

Virtual Data Labelling information

See salary details

$46K

$165K

$243.5K

How much do virtual data labelling jobs pay per year?

As of Aug 4, 2026, the average yearly pay for virtual data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

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

AspectVirtual Data LabellingData Annotation Specialist
CredentialsBasic computer skills, training in labelling toolsSimilar, often requires training in annotation software
Work EnvironmentRemote, online platformsRemote or on-site, depending on employer
Industry UsageAI, machine learning, autonomous vehiclesAI, computer vision, NLP projects
Search IntentLabeling data for AI modelsAnnotating data for machine learning

Both roles involve preparing data for AI systems, but Virtual Data Labelling focuses on assigning labels to datasets using online tools, while Data Annotation Specialists may perform more detailed annotations, often requiring specific domain knowledge. Both are essential in AI development and share similar work environments and skill requirements.

What is virtual data labelling?

Virtual data labelling is the process of annotating or tagging data, such as images, videos, or text, through online platforms to make it understandable for machine learning algorithms. Data labelers work remotely to identify and categorize objects, features, or information within datasets, which helps train artificial intelligence systems. This job is essential in industries like autonomous vehicles, healthcare, and e-commerce, where large volumes of labelled data are needed to improve AI accuracy.

How does a virtual data labeller typically collaborate with data scientists and machine learning engineers?

Virtual data labellers play a crucial role in supporting data scientists and machine learning engineers by accurately tagging data that will be used to train and validate models. Collaboration often occurs through project management tools or direct communication platforms, where labellers receive guidelines and feedback to ensure consistency and quality. Regular check-ins or quality audits are common, and labellers may join virtual meetings to clarify requirements or discuss ambiguous cases. This teamwork helps ensure that the labelled data meets project standards and contributes to the success of AI initiatives.

What are the key skills and qualifications needed to thrive as a virtual data labeller, and why are they important?

To thrive as a Virtual Data Labeller, you need strong attention to detail, accuracy, and basic data processing skills, typically supported by a high school diploma or relevant experience. Familiarity with data annotation tools, content management systems, and sometimes basic programming or spreadsheet software is important. Strong time management, focus, and effective communication skills help you meet deadlines and collaborate with remote teams. These abilities are crucial to ensure high-quality, consistent data labelling that directly impacts the performance of machine learning models.
More about Virtual Data Labelling jobs
What cities are hiring for Virtual Data Labelling jobs? Cities with the most Virtual Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Virtual Data Labelling jobs? States with the most job openings for Virtual Data Labelling jobs include:
What job categories do people searching Virtual Data Labelling jobs look for? The top searched job categories for Virtual Data Labelling jobs are:
Infographic showing various Virtual Data Labelling job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Director, Simulation and Evaluation - Autonomous Driving

Bosch Group

Sunnyvale, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago


Job description

Company Description

We Are Bosch.

At Bosch, we shape the future by inventing high-quality technologies and services that spark 
enthusiasm and enrich people's lives. Our areas of activity are every bit as diverse as our outstanding 
Bosch teams around the world. Their creativity is the key to innovation through connected living, 
mobility, or industry. 

Let's grow together, enjoy more, and inspire each other. Work #LikeABosch
Reinvent yourself: At Bosch, you will evolve. 
Discover new directions: At Bosch, you will find your place. 
Balance your life: At Bosch, your job matches your lifestyle. 
Celebrate success: At Bosch, we celebrate you. 
Be yourself: At Bosch, we value values. 
Shape tomorrow: At Bosch, you change lives.

"Invented for Life" drives us at Bosch and our vision of future mobility. Autonomous vehicles will change the way we move and at Bosch we are working on making this future a reality. We are now growing our team to solve some of the hardest automated driving problems, and are looking for experts for product engineering of AI-based Autonomous Driving systems.

Job Description

As the Director for Simulation and Evaluation, you will sit at the center of the Global AI Backbone, architecting the multi-level simulation ecosystems required to train, evaluate and validate next-generation Foundation Models. You will bridge the gap between high-fidelity sensor simulation and generative world models, ensuring our AI systems are statistically proven to be safe and robust before hitting the road.


This is a global role that requires you to define and manage a global simulation and evaluation ecosystem that enables continuous development and deployment of our ADAS systems.


Key Responsibilities:

  • Lead AI Simulation & Foundation Model Strategy: Define the roadmap for high throughput, closed-loop simulation.
  • Research and propose new methodologies to assess the quality, safety, and realism of ML models used for training, evaluation and validation of L2++ and L4 automated driving stacks.
  • Architect Evaluation Frameworks: Build the infrastructure. Develop tools that allow for rapid iteration of Foundation Models, ensuring model improvements translate into measurable gains in fleet-wide performance.
  • Drive Generative AI Innovation: Lead the development of World Models to predict and generate complex, realisticedge cases. Build data pipelines for signal discovery, data  labeling, and metric computation based on large-scale simulations.
  • Production Release Authority: Establish the "gold standard" for evaluation that informs SoP (Start of Production) and model release decisions. Translate complex simulation data into technical strategy documentation for executive decision-making.
  • Global Technical Leadership: Lead, mentor and inspire a cross-functional global team of SWEs, Data Scientists, and ML experts, fostering a culture of rigorous statistical validation and innovative engineering.
Qualifications

Basic Qualifications:

  • Master's or PhD in Computer Science, Electrical Engineering, Machine Learning, Statistics, Physics, or a related quantitative field.
  • 10+ years of experience in software engineering, with a specific focus on embedded systems, automotive, or robotics.
  • 7+ years of experience leading complex software projects from concept to production within the ADAS or Autonomous Driving domain.
  • Direct, hands-on experience with L2++ or L4 system Start of Production (SoP), specifically overseeing simulation, testing, and validation protocols for high-stakes deployments.
  • 5+ years of involvement with the development or evaluation of large-scale AI, LLMs, or World Models/Generative AI models for simulation and behavioral prediction.
  • Expert-level understanding of multi-level simulation platforms, including high-fidelity sensorlevel simulation for perception and scalable object-level simulation for behavioral training.
  • Proven mastery of data-driven report writing and technical strategy documentation designed for executive decision-making and safety case justifications.

Preferred Qualifications:

  • 5+ years of experience with high-throughput simulation, GPU-accelerated technologies (CUDA), parallel computing, and Reinforcement Learning (RL).
  • Mastery of C++ and Python. Experience building automated data pipelines for signal discovery, data labeling, and large-scale metric computation.
  • 5+ years of experience managing and mentoring global, multi-disciplinary teams of Software Engineers, Data Scientists, and ML experts.
  • Working knowledge of automotive industry safety standards and regulations (e.g., ISO 26262, SOTIF) as they apply to virtual validation.
Additional Information

Equal Opportunity Employer, including disability / veterans 

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. 

The U.S. base salary range for this full-time position is between $240,000-300,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. This range does not include annual bonus percentage nor any other monetary considerations for the total compensation package. Your Recruiter can share more details about the specific salary range for this position during the interview process.
In addition to your base salary, Bosch offers a comprehensive benefits package that includes health, dental, and vision plans; health savings accounts (HSA); flexible spending accounts; 401(K) retirement plan with an attractive employer match; wellness programs; life insurance; long term disability insurance; paid time off; parental leave. Pay ranges included in the postings, when included, generally reflect base salary; certain positions may include bonus, or additional benefits.

#LI-JGM1 #selfdriving #hybridjobs #AV #autonomoussystems