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Data Labelling Jobs in Boston, MA (NOW HIRING)

AgZen

Senior Data Scientist

Somerville, MA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Define and implement scalable data quality measures across complex, multimodal data labeling pipelines * Contribute to an organization wide data ontology and class structure for perception models

Agzen

Senior Data Scientist

Somerville, MA · On-site

$150 - $180/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Define and implement scalable data quality measures across complex, multimodal data labeling pipelines * Contribute to an organization wide data ontology and class structure for perception models

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All JobsData Labelling JobsData Labelling Jobs in Boston, MA

Data Labelling information

See Boston, MA salary details

$50K

$179.3K

$264.5K

How much do data labelling jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data labelling in Boston, MA is $179,276.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,000.00 and $184,700.00 per year, depending on experience, location, and employer.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

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

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with common tools like labeling software and understand data annotation standards. Building attention to detail and basic knowledge of the data types you will label, such as images or text, is essential. Many entry-level roles require no formal certification but may prefer candidates with basic computer skills and the ability to follow detailed instructions.

How much do data labelers get paid?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Some positions may offer project-based pay or bonuses for accuracy and efficiency.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and may be performed remotely or in a controlled environment.

What are the most commonly searched types of Data Labelling jobs in Boston, MA?

The most popular types of Data Labelling jobs in Boston, MA are:

What are popular job titles related to Data Labelling jobs in Boston, MA?

For Data Labelling jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Data Labelling jobs in Boston, MA look for?

The top searched job categories for Data Labelling jobs in Boston, MA are:

Data Labelling jobs near you
Infographic showing various Data Labelling job openings in Boston, MA as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $179,276 per year, or $86.2 per hour.

Senior Data Scientist - Data for Perception Machine Learning

Zoox

Boston, MA • On-site

$190K - $258K/yr

Full-time

Medical, Life, PTO

Re-posted 24 days ago

Job description

We are seeking an experienced and highly skilled data scientist to join the Perception Data and Labeling team.. The team is responsible for training and evaluation data powering the perception (vision, lidar, and other modalities) ML models at Zoox. The candidate will work alongside data ops partners, ML engineers, software developers, and data engineers to improve model performance through high quality human- and auto-labeled data.
In this role, you will:
  • Define and implement scalable data quality measures across complex, multimodal data labeling pipelines
  • Drive data-centric ML model improvements to achieve critical Zoox milestones
  • Support an org-wide data ontology and class structure for perception models
  • Determine trade-offs and integrations between human-labeled, human-in-the-loop, and zero-shot autolabeled data
  • Build metrics to quantify labeling throughput, capacity, and annotator/vendor quality
Qualifications:
  • Master's or PhD degree in a field relevant to autonomous driving (computer science, robotics) to the analysis of human data (computational neuroscience, cognitive science) or a related field
  • Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code
  • Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business.
  • Background in statistical modeling and analysis; including experience making data-driven decisions that connect point and uncertainty estimates to business impact.
  • Experience with data-centric ML development and data curation
Bonus Qualifications:
  • Experience with experiment design and statistical comparisons (A/B testing, parametric/non-parametric statistics, etc.)
  • Experience with human data collection, including annotation task design
$190,000 - $258,000 a year
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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