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Data Tagger Jobs (NOW HIRING)

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102.20K - $140.40K/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 ...

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 ...

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 ...

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 ...

Use tools like Sprout Social Influencer/Tagger, SullyGnome/TwitchMetrics, Gospel Stats, and AI ... Translate data into stories clients understand and believe in * Stay on top of platform shifts ...

... tagger guns, tape machine, small hand tools, ladders, step stools, hand truck/dolly, baler ... data entry skills * Ability to work in a flexible environment, shift quickly as our business ...

... tagger. Essential Duties and Responsibilities: * Reads production schedule, customer order, work ... Experience with data entry and inventory management systems preferred. * Ability to pass and ...

Collaborate with Analytics team to ensure all data and metrics are collected appropriately to ... Tagger, Captiv8, CreatorIQ or AdobeSuite). Salary range: $50,000 USD - $55,000 USD Where an ...

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Data Tagger information

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 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.

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.

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.

More about Data Tagger jobs
What cities are hiring for Data Tagger jobs? Cities with the most Data Tagger job openings:
What states have the most Data Tagger jobs? States with the most job openings for Data Tagger jobs include:
Infographic showing various Data Tagger job openings in the United States as of May 2026, with employment types broken down into 56% Full Time, 33% Part Time, and 11% Contract. Highlights an 89% In-person, and 11% Remote job distribution.
Senior, ML Engineer - Auto Tagger

Senior, ML Engineer - Auto Tagger

Torc Robotics

Ann Arbor, MI

$102.20K - $140.40K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Job description

About the Company 

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.   

Meet The Team: 

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 mining driving logs for long-tail events, we provide the foundational data required for safe autonomous trucking. Leveraging Pegasus logical layers, this team structures and catalogs findings into an observations database that directly accelerates development across autonomous perception, sensor fusion, and generative simulation testing. 

What You'll Do: 

  • Scenario Mining at Scale: 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.
  • Advanced Event Tagging: 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.
  • Standardized Data Structuring: Extract and format scenario data utilizing the Pegasus layer standard (alongside opensource frameworks) to ensure semantic consistency and rigorous metadata integrity.
  • Data Flywheel Integration: Manage the ingestion of tagged events into the observations database, enabling high-speed querying and retrieval for ML training, regression testing, and system validation.
  • Cross-Functional Alignment: 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.
  • Mentorship & Team Growth: Guide, mentor, and elevate less-experienced engineers. Lead design reviews, establish coding standards, and foster a culture of technical excellence and collaborative problem-solving. 

What You'll Need to Succeed: 

  • BS or MS in Computer Science, Robotics, Engineering, or a STEM field, with 6+ years in data engineering, ML systems, or autonomous data curation.
  • Core Languages: Strong Python and SQL skills, with heavy experience processing massive time-series or unstructured datasets.
  • ML & Dataset Curation: Hands-on machine learning and dataset curation experience, with a demonstrated history of implementing targeted datasets that measurably improve downstream model performance.
  • Data Exploration: Hands-on experience using Databricks (or similar platforms) for large-scale analytics, interactive querying, and making massive vehicle datasets searchable.
  • Cloud & Compute: Expertise in distributed compute frameworks (Ray, Spark, Beam) and cloud platforms (AWS, GCP, or Azure) for executing heavy data workloads.
  • AV Standards: Experience parsing complex data formats and applying scenario-description standards like Pegasus layers.
  • Communication: Exceptional ability to translate complex data engineering challenges into clear strategies for cross-functional stakeholders.
  • Technical Leadership: Proven track record of mentoring teams, driving system architecture, and defining engineering roadmaps. 

Bonus Points! 

  • Auto-labeling & VLMs: Familiarity with foundational models, auto-labeling pipelines, or zero-shot classification for scenario extraction.
  • Model Serving: Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference
  • Semantic Inference: Experience with semantic extraction and attribute mapping to help build out a robust semantic inference engine, moving beyond standard bounding-box object detection.
  • Data Tooling: Familiarity with parsing robotics formats (ROS bags, MCAP) and optimizing high-performance columnar storage formats (Parquet, Arrow).
  • Downstream Integration: Knowledge of how scenario data feeds into generative simulation workflows, neural rendering, or sensor fusion validation.
  • Advanced Retrieval: Experience building semantic retrieval systems or vector databases for automotive data. 

Perks of Being a Torc'r 

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers: 

  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (availableimmediately after start date)
  • Company-wide holiday office closures
  • AD+D and Life Insurance 

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply. 

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. 

Job ID: R-102717