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Data Annotation Engineer Jobs in Boston, MA (NOW HIRING)

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Contribute to software architecture, code reviews, and engineering best practices to ensure ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Contribute to software architecture, code reviews, and engineering best practices to ensure ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Contribute to software architecture, code reviews, and engineering best practices to ensure ...

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Showing results 1-20

All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Boston, MA

Data Annotation Engineer information

See Boston, MA salary details

$55.9K

$160.2K

$214K

How much do data annotation engineer jobs pay per year?

As of Jul 23, 2026, the average yearly pay for data annotation engineer in Boston, MA is $160,193.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,300.00 and $212,900.00 per year, depending on experience, location, and employer.

What are the main challenges faced by Data Annotation Engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

Does data annotation really pay?

Data annotation engineers can earn competitive wages, often paid hourly or per task, with pay rates varying based on experience, complexity of annotations, and the platform or employer. Entry-level roles may start at minimum wage, while experienced annotators or those with specialized skills can earn higher salaries or freelance rates. Overall, data annotation can provide a reliable income, especially for remote or flexible work arrangements.

What is the highest salary for data annotator?

The highest salary for a data annotation engineer can reach up to $80,000 to $100,000 annually, depending on experience, location, and the complexity of annotation tasks. Senior roles or those with specialized skills in tools like Labelbox or CVAT may earn higher compensation. Salaries vary widely across companies and regions but generally reflect the technical skills required for high-quality data labeling.

What is a data annotation engineer?

A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to prepare it for machine learning models. They often use specialized tools and follow guidelines to ensure data quality, supporting the development of AI systems.

How hard is it to get hired by data annotation?

Getting hired as a data annotation engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require advanced degrees, but strong accuracy and consistency are important for success in the role.

What is a Data Annotation Engineer job?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Boston, MA? For Data Annotation Engineer jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Boston, MA look for? The top searched job categories for Data Annotation Engineer jobs in Boston, MA are:
Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Boston, MA as of July 2026, with employment types broken down into 69% Full Time, 12% Part Time, and 19% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $160,193 per year, or $77 per hour.
Data Scientist Contractor, Computational Biology

Data Scientist Contractor, Computational Biology

CAMP4 Therapeutics

Cambridge, MA

$64K - $64K/yr

Contractor

Posted 27 days ago

Job description

Position Title: Data Scientist Contractor, Computational Biology (6-month contract)
Reports To: Senior Director, Head of Data Sciences
Location: Cambridge, MA
Join the adventure!
CAMP4 is seeking a Data Science Contractor for a 6-month temporary contract assignment, specializing in Computational Biology, Bioinformatics, or Systems Biology, to support the processing, analysis, visualization, and interpretation of next-generation sequencing datasets. This assignment will have a particular focus on RNA-seq, scRNAseq, and long-read sequencing data, including Nanopore and PacBio platforms.
The successful candidate will apply state-of-the-art computational tools and, where needed, develop fit-for-purpose analytical approaches to interrogate complex genomics datasets. This role will help generate focused biological hypotheses to support target identification, target validation, and drug discovery programs. The candidate will work closely with experimental biologists and data scientists to systematically apply hypothesis-driven genomics approaches to advance CAMP4’s understanding of transcriptional mechanisms of disease and therapeutic strategies derived from them.

Key Responsibilities:
  • Process, analyze, visualize, and interpret next-generation sequencing (NGS) datasets, with an emphasis on bulk RNA-seq, scRNAseq, and long-read RNA sequencing, including Nanopore and PacBio sequencing data.
  • Execute bioinformatics analyses according to predefined analysis plans, including quality control, alignment, quantification, differential expression analysis, isoform/transcript analysis, splicing analysis, and integrative interpretation of results.
  • Collaborate closely with cross-functional teams, including experimental biologists, computational scientists, and project teams, to develop, refine, and execute research plans.
  • Provide clear biological interpretation and scientific context for computational results to support target discovery, validation, and mechanistic understanding.
  • Evaluate, implement, and apply new bioinformatics methods, tools, and emerging technologies relevant to transcriptomics, long-read sequencing, and functional genomics.
  • Develop scripts, workflows, and software tools where gaps exist to enable reproducible and scalable data analysis.
  • Provide conceptual input into analysis plans, including analytical strategy, study design, prioritization, and interpretation of key results.
  • Participate in cross-functional discussions to refine project goals, identify key priorities, and communicate findings effectively to both computational and experimental scientists.
  • Demonstrate strong ownership, attention to detail, and a sense of urgency in delivering high-quality analyses that support the discovery of breakthrough medicines for patients.
Qualifications:
Education amp; Experience
  • PhD in Bioinformatics, Computational Biology, Systems Biology, or a related field with 3+ years of relevant industry or postdoctoral experience.
Skills amp; Competencies
  • Strong hands-on experience analyzing NGS datasets, especially RNA-seq, scRNAseq, and long-read sequencing data from Nanopore and/or PacBio platforms.
  • Familiarity with long-read sequencing tools and workflows for transcript discovery, isoform characterization, or full-length transcript analysis is highly desirable.
  • Experience with additional functional genomics datasets, such as ATAC-seq, ChIP-seq, and PRO-seq.
  • Solid background in statistics and strong programming skills in Python and/or R.
  • Experience working in a Linux environment and using high-performance computing clusters and/or cloud computing platforms such as AWS.
  • Familiarity with human genome annotation resources, biological pathway databases, and systems biology concepts.
  • Strong commitment to reproducible research, best practices in software development, documentation, and version control.
  • Excellent collaboration and communication skills, with the ability to explain computational results clearly to experimental scientists and cross-functional teams.
  • Strong attention to detail, high professional integrity, and commitment to excellence in execution.
  • Creative and solution-oriented with the ability to develop fit-for-purpose approaches for diverse data and project needs.
  • Passionate about applying computational biology and genomics to translate fundamental scientific discoveries into medicines that improve patients’ lives.
Compensation:
Pay rate for this role will be determined based on the candidate’s skills and experience.

About CAMP4:
CAMP4 is developing disease-modifying treatments for a broad range of genetic diseases where amplifying healthy protein may offer therapeutic benefits. Our approach amplifies mRNA by harnessing a fundamental mechanism of how genes are controlled. To amplify mRNA, our therapeutic ASO drug candidates target regulatory RNAs (regRNAs), which act locally on transcription factors and are the master regulators of gene expression. CAMP4’s proprietary RAPTM Platform enables the mapping of regRNAs and design of optimal chemistry to generate potent therapeutic candidates to address hundreds of genetic diseases across multiple tissues. Learn more about us at www.camp4tx.com and follow us @CAMP4tx.

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