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Annotation Labelling Jobs in Boston, MA (NOW HIRING)

IPG Photonics

Intern, Engineering

Marlborough, MA · On-site

$17.25 - $22.50/hr

Strong attention to detail, especially for image labeling and data accuracy * Interest in machine learning, data annotation, or computer vision concepts * Experience with MS Office products (Word ...

Evolv Technology

Sr. Data Infrastructure Engineer

Waltham, MA · On-site

$123.50K - $148.30K/yr

Integrate with data labeling services and annotation workflows. * Enable efficient access patterns for large‑scale ML workloads. AWS‑Based Cloud Infrastructure: * Build and optimize pipelines ...

Evolv Technology

Sr. Data Infrastructure Engineer

Watertown, MA · On-site

$124.50K - $149.50K/yr

Integrate with data labeling services and annotation workflows. * Enable efficient access patterns for large‑scale ML workloads. AWS‑Based Cloud Infrastructure: * Build and optimize pipelines ...

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Annotation Labelling information

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Boston, MA? For Annotation Labelling jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Boston, MA look for? The top searched job categories for Annotation Labelling jobs in Boston, MA are:
Annotation Labelling jobs near you
Postdoctoral Associate, Neurology, Boston University Chobanian & Avedisian School of Medicine

Postdoctoral Associate, Neurology, Boston University Chobanian & Avedisian School of Medicine

Boston University

Boston, MA • On-site

$70K/yr

Full-time

Posted 29 days ago

Boston University rating

7.9

Company rating: 7.9 out of 10

Based on 51 frontline employees who took The Breakroom Quiz

174th of 532 rated colleges and universities

Job description

Job Description
Location: Boston University School of Medicine (Boston, MA)
Supervisors: Jesse Mez, MD, MS; Jon Cherry, PhD; Vijay K. Kolachalama, PhD
Position summary
We seek a motivated postdoctoral research fellow to join an interdisciplinary team investigating post traumatic neurodegeneration using digital neuropathology whole slide images (WSIs), clinical phenotypes, and machine learning. The fellow will play a central "bridge" role between neuropathology, clinical neurology, and data science, working across brain bank cohorts (UNITE, Framingham Heart Study, and the BU ADRC) to develop and validate computational classifiers and to link image derived pathology features with lifetime clinical data. The position is ideal for a candidate with a strong neuroscience background-particularly in head trauma and/or neurodegenerative disease-who wants to combine wet lab neuropathologic techniques with computational model development and translational analyses.
Project overview
This NIH funded project leverages WSIs and richly phenotyped cohorts to: develop algorithms to detect neuropathologic signatures of chronic traumatic encephalopathy (CTE); identify neuropathologic features associated with repetitive head impact (RHI) exposure; and map pathology patterns to clinical outcomes observed in life (cognitive impairment, behavioral dysregulation, parkinsonism, etc.). The fellow will help build and curate image datasets, generate and validate annotations and experimental labels, design and apply machine learning/image analysis pipelines, and integrate pathology features with clinical and epidemiologic data across cohorts to address these aims.
Key responsibilities
  • Lead development, evaluation, and refinement of machine learning and image analysis pipelines for WSIs, including preprocessing, annotation workflows, model training/validation, and interpretability analyses.
  • Curate and harmonize WSI datasets and associated metadata from multiple brain banks; contribute to quality control
  • Design and perform targeted wet lab neuropathologic experiments (e.g., immunohistochemistry, staining optimization, region specific sampling) to validate computational findings and generate ground truth labels as needed.
  • Integrate pathology derived quantitative features with clinical and cohort data to test associations with RHI exposure and clinical phenotypes; collaborate on statistical analyses.
  • Collaborate closely with neuropathologists, clinicians, and computational scientists to interpret findings in a neuropathologic and clinical context, and iteratively improve models.
  • Maintain reproducible, well documented workflows (code, pipelines, notebooks) and manage data in accordance with BU policies and grant requirements.
  • Disseminate results through manuscripts, grant reports, and presentations; assist with mentoring trainees and coordinating with collaborators.

Application instructions
Please submit a single PDF to Dr. Jesse Mez at jessemez@bu.edu containing:
  1. Cover letter describing your interest and relevant experience across neuropathology, neurology, and data science, and how you envision bridging wet lab and computational work.
  2. Curriculum vitae (with publication list).
  3. Contact information for three references (one should be your PhD/postdoc advisor or equivalent).
  4. Representative papers, or other relevant work samples.

Review of applications will begin immediately and continue until the position is filled.
Required Skills
Qualifications
Required
  • PhD, MD/PhD, or equivalent doctoral degree in neuroscience, neuropathology, computational biology, biomedical engineering, computer science with neuroscience focus, or closely related field.
  • Demonstrated neuroscience background with interest in head trauma and/or neurodegenerative disease.
  • Experience in at least one of the following: neuropathologic methods (histology/IHC), digital pathology/WSI workflows, or machine learning for biomedical images.
  • Strong written and oral communication skills and proven ability to work effectively in interdisciplinary teams.
  • Track record of scholarly productivity (publications, preprints, or substantial project deliverables).

Preferred
  • Programming proficiency in Python and/or R; experience with deep learning frameworks (PyTorch, TensorFlow) preferred.
  • Prior experience working with whole slide image formats, slide scanners, annotation tools (HALO, QuPath, ASAP, SlideRunner, etc.), and image pre processing.
  • Experience integrating multi modal datasets (pathology images, clinical, epidemiologic cohorts).
  • Familiarity with neuropathologic features and proteinopathies (tau, TDP 43, amyloid, alpha synuclein).
  • Hands on wet lab histology or IHC experience.
  • Prior involvement with brain bank data or large longitudinal cohort studies.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, natural or protective hairstyle, religion, sex, age, national origin, physical or mental disability, sexual orientation, gender identity, genetic information, military service, pregnancy or pregnancy-related condition, or because of marital, parental, or veteran status. We are a VEVRAA Federal Contractor.

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Boston University is an international, comprehensive, private research university, committed to educating students to be reflective, resourceful individuals ready to live, adapt, and lead in an interconnected world. Boston University is committed to generating new knowledge to benefit society. We remain dedicated to our founding principles: that higher education should be accessible to all and that research, scholarship, artistic creation, and professional practice should be conducted in the service of the wider community—local and international. These principles endure in the University’s insistence on the value of diversity, in its tradition and standards of excellence, and in its dynamic engagement with the City of Boston and the world. Boston University comprises a remarkable range of undergraduate, graduate, and professional programs built on a strong foundation of the liberal arts and sciences. With the support and oversight of the Board of Trustees, the University, through our faculty, continually innovates in education and research to ensure that we meet the needs of students and an ever-changing world.

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10,000+ Employees

Headquarters location

Boston, MA, US

Year founded

1839

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