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Data Labelling Jobs in Massachusetts (NOW HIRING)

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

Senior Data Scientist

Somerville, MA · On-site

$150 - $180/hr

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

Showing results 41-60

Data Labelling information

See Massachusetts salary details

$50.2K

$180.2K

$265.9K

How much do data labelling jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data labelling in Massachusetts is $180,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,800.00 and $185,700.00 per year, depending on experience, location, and employer.

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 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.

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.

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.

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.

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.

What are the most commonly searched types of Data Labelling jobs in Massachusetts?

The most popular types of Data Labelling jobs in Massachusetts are:

What are popular job titles related to Data Labelling jobs in Massachusetts?

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

What job categories do people searching Data Labelling jobs in Massachusetts look for?

The top searched job categories for Data Labelling jobs in Massachusetts are:

What cities in Massachusetts are hiring for Data Labelling jobs?

Cities in Massachusetts with the most Data Labelling job openings:

Infographic showing various Data Labelling job openings in Massachusetts as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 100% In-person job distribution, with an average salary of $180,220 per year, or $86.6 per hour.

Senior Machine Learning Data Engineer - Cambridge

Motion Recruitment Partners, LLC

Cambridge, MA • On-site

$125K - $150K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Job description


A fast-growing robotics company is seeking a Senior Machine Learning Data Engineer to help develop the data foundation that powers intelligent robotic systems operating in high-throughput logistics environments. The organization builds AI-driven automation solutions that leverage computer vision, machine learning, and robotic manipulation to solve complex real-world challenges involving package handling, object identification, and operational optimization.
As a Senior Machine Learning Data Engineer, you will focus on the collection, preparation, management, and delivery of data used to train, evaluate, and improve machine learning models. Unlike traditional data engineering positions that concentrate on analytics, reporting, or platform infrastructure, this role is centered on enabling AI and computer vision teams to build more accurate and effective robotic systems.
You will work closely with machine learning engineers, roboticists, software developers, and product teams to create scalable data pipelines capable of handling large volumes of image, video, sensor, and operational data. The ideal candidate enjoys solving challenges surrounding data labeling, feature generation, model training datasets, data versioning, and machine learning infrastructure. This role offers the opportunity to directly influence how AI systems learn and improve within a cutting-edge robotics environment.
Required Skills & Experience
  • Strong proficiency with Python and SQL
  • Experience building data pipelines for machine learning workloads
  • Experience working with large-scale image, video, or sensor datasets
  • Knowledge of data processing frameworks such as Spark or Ray
  • Experience with cloud platforms such as AWS
  • Understanding of data modeling and storage solutions for ML applications
  • Experience building ETL workflows and automation solutions
  • Familiarity with machine learning lifecycle concepts
  • Experience with version control and software engineering best practices
  • Strong problem-solving and analytical skills

Desired Skills & Experience
  • 5+ years of Data Engineering or Machine Learning Infrastructure experience
  • Experience supporting computer vision or AI-focused teams
  • Robotics, automation, or industrial technology experience
  • Familiarity with model training workflows and feature engineering
  • Experience with annotation platforms and data labeling operations
  • Knowledge of MLOps tools and practices
  • Experience working with unstructured datasets
  • Bachelor's degree in Computer Science, Data Engineering, Engineering, Mathematics, or a related field

What You Will Be Doing
Daily Responsibilities
  • 100% Hands On
  • Build and maintain machine learning data pipelines supporting robotics and AI initiatives
  • Develop processes that prepare image, video, and sensor datasets for model training
  • Partner with machine learning teams to improve the quality and accessibility of training data
  • Design scalable storage and retrieval solutions for large unstructured datasets
  • Create data validation processes that improve model reliability and performance
  • Support feature engineering, experimentation, and dataset generation workflows
  • Implement automation that reduces manual effort in data preparation and curation
  • Monitor data pipelines and resolve issues impacting model development
  • Optimize data processing workflows for performance and scalability
  • Contribute to the evolution of machine learning infrastructure and data best practices

The Offer
  • Bonus OR Commission eligible

You will receive the following benefits
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)
  • 401(k) (including match, if applicable)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.