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Data Tagger Jobs (NOW HIRING)

Torc Robotics

Senior, ML Engineer - Auto Tagger

$107K - $146K/yr

The Senior ML Engineer - Auto Tagger will be responsible for architecting data pipelines and developing algorithms to optimize the processing of vehicle data, ensuring data integrity and facilitating ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

The Auto Tagger team is the engine behind our data flywheel, responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios. By ...

Evergy

Operations Apprentice II

Burlington, KS

$14.25 - $18.50/hr

... tagger and fire brigade. * The Operations Apprentice II primary responsibility is to learn building ... Review all operating data in the assigned work area to assure safe operations. Effectively ...

Evergy

Operations Apprentice II

Burlington, KS · On-site

$14.25 - $18.50/hr

... tagger and fire brigade. * The Operations Apprentice II primary responsibility is to learn building ... operating data in the assigned work area to assure safe operations. • Effectively communicate ...

Evergy

Operations Apprentice II

Burlington, KS · On-site

$14.25 - $18.50/hr

... tagger and fire brigade. * The Operations Apprentice II primary responsibility is to learn building ... Review all operating data in the assigned work area to assure safe operations. Effectively ...

Balance Staffing - Stockton

Warehouse Clerk

Stockton, CA · On-site

$18/hr

... Pallet Tagger/Warehouse Clerk for a short-term contract opportunity in Stockton. This role is ... Enter data accurately into company systems * Perform frequent addition and subtraction to verify ...

Academy School District 20

Understanding of data privacy laws and their implications for the educational community Work Environment: The work environment characteristics described here are representative of those a staff ...

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Data Tagger information

What is a data tagging job?

A data tagging job involves labeling or annotating data, such as images, videos, or text, to help machine learning models understand and process information. Workers typically use specialized tools to add tags according to specific guidelines and may need attention to detail and basic technical skills. This role is often performed remotely and can be part-time or freelance.

Do data entry jobs really pay?

Data tagger jobs typically pay hourly wages that vary depending on experience, location, and employer, with rates often ranging from minimum wage to higher amounts for experienced workers. Many data tagging roles are entry-level and may offer part-time or flexible schedules, but pay rates are generally consistent with other data entry positions. Accurate and efficient work can lead to higher earnings or bonuses in some cases.

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

To thrive as a Data Tagger, you need keen attention to detail, strong analytical skills, and familiarity with labeling guidelines, often backed by a high school diploma or relevant experience. Proficiency with data annotation platforms, spreadsheets, and sometimes basic knowledge of programming or machine learning tools is common. Effective communication, reliability, and the ability to concentrate for extended periods help someone excel in this role. These skills ensure that datasets are accurately labeled, which is critical for training high-quality AI and machine learning models.

What are Data Taggers?

Data Taggers are professionals who label or annotate data, such as images, text, audio, or video, to make it usable for machine learning models. Their work involves identifying and marking specific features or objects within datasets, ensuring that artificial intelligence systems can learn from accurately labeled information. Data tagging is critical in training algorithms for tasks like image recognition, natural language processing, and autonomous driving. Attention to detail and consistency are important skills for this role.

Which 3 jobs will survive AI?

Data taggers are likely to be replaced by AI systems that can automate data labeling and annotation tasks. Jobs that require complex human judgment, creativity, or emotional intelligence—such as healthcare professionals, creative designers, and mental health counselors—are more likely to persist. Skills in managing, supervising, or developing AI tools will also remain valuable.

What is the difference between Data Tagger vs Data Annotator?

AspectData TaggerData Annotator
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentData labeling platforms, remote or on-siteData labeling platforms, remote or on-site
Industry UsageAI, machine learning, data processingAI, machine learning, data processing
Search & Comparison IntentYesYes

Both Data Taggers and Data Annotators work in AI and machine learning fields, often performing similar tasks like labeling data. The main difference lies in terminology used by different companies or platforms, but their roles, skills, and work environments are largely overlapping. Understanding these terms can help job seekers find relevant opportunities in data labeling and annotation roles.

Is 40 too late for data science?

For a Data Tagger or similar entry-level data roles, age is generally not a barrier; skills, relevant experience, and training are more important. Many professionals transition into data science or related fields later in their careers by acquiring necessary skills such as programming, statistics, and tools like Python or SQL. Age should not prevent pursuing a career in data science if you are committed to learning and developing relevant expertise.

What are some common challenges faced by Data Taggers and how can they be managed?

Data Taggers often encounter challenges such as repetitive tasks, maintaining high accuracy, and meeting tight deadlines. To manage these, it's important to develop strong attention to detail and take regular breaks to avoid fatigue. Collaborative communication with team members and supervisors can also help clarify ambiguous data points and improve overall data quality. Many organizations provide training sessions and quality assurance feedback to support continuous improvement in this role.
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Data Tagger jobs near you
Infographic showing various Data Tagger job openings in the United States as of July 2026, with employment types broken down into 50% Part Time, and 50% Contract. Highlights an 50% In-person, and 50% Remote job distribution.
Senior, ML Engineer - Auto Tagger

Senior, ML Engineer - Auto Tagger

Torc Robotics

Remote

$107K - $146K/yr

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The Senior ML Engineer - Auto Tagger will be responsible for architecting data pipelines and developing algorithms to optimize the processing of vehicle data, ensuring data integrity and facilitating collaboration across teams.
Responsibilities:
• Architect and optimize distributed data pipelines to process massive multi-sensor logs (camera, LiDAR, radar, kinematics), automatically extracting and cataloging safety-critical and long-tail driving events.
• Develop and tune both heuristic-based and ML-assisted algorithms (including exploring Vision-Language Models or semantic vector search) to automatically classify and describe complex environmental and behavioral scenarios.
• Extract and format scenario data utilizing the Pegasus layer standard (alongside opensource frameworks) to ensure semantic consistency and rigorous metadata integrity.
• Manage the ingestion of tagged events into the observations database, enabling high-speed querying and retrieval for ML training, regression testing, and system validation.
• Operate with broad autonomy to drive consensus across organizational boundaries.
• Collaborate closely with downstream consumers in perception, simulation, and systems engineering to define what constitutes an 'interesting scenario' and operationalize a continuous data loop.
• Guide, mentor, and elevate less-experienced engineers.
• Lead design reviews, establish coding standards, and foster a culture of technical excellence and collaborative problem-solving.
Qualifications:
Required:
• BS or MS in Computer Science, Robotics, Engineering, or a STEM field, with 6+ years in data engineering, ML systems, or autonomous data curation.
• Strong Python and SQL skills, with heavy experience processing massive time-series or unstructured datasets.
• Hands-on machine learning and dataset curation experience, with a demonstrated history of implementing targeted datasets that measurably improve downstream model performance.
• Hands-on experience using Databricks (or similar platforms) for large-scale analytics, interactive querying, and making massive vehicle datasets searchable.
• Expertise in distributed compute frameworks (Ray, Spark, Beam) and cloud platforms (AWS, GCP, or Azure) for executing heavy data workloads.
• Experience parsing complex data formats and applying scenario-description standards like Pegasus layers.
• Exceptional ability to translate complex data engineering challenges into clear strategies for cross-functional stakeholders.
• Proven track record of mentoring teams, driving system architecture, and defining engineering roadmaps.
Preferred:
• Familiarity with foundational models, auto-labeling pipelines, or zero-shot classification for scenario extraction.
• Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference.
• Experience with semantic extraction and attribute mapping to help build out a robust semantic inference engine, moving beyond standard bounding-box object detection.
• Familiarity with parsing robotics formats (ROS bags, MCAP) and optimizing high-performance columnar storage formats (Parquet, Arrow).
• Knowledge of how scenario data feeds into generative simulation workflows, neural rendering, or sensor fusion validation.
• Experience building semantic retrieval systems or vector databases for automotive data.
Company:
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships Founded in 2005, the company is headquartered in Blacksburg, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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