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Medical Image Annotation Jobs in Needham, MA (NOW HIRING)

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Experience with OCT, IVUS, CT, MRI or other medical imaging modalities, including multi-modal image ...

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Experience with OCT, IVUS, CT, MRI or other medical imaging modalities, including multi-modal image ...

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Own end-to-end ML lifecycle, including data preparation, annotation strategies, model development ... Experience with OCT, IVUS, CT, MRI or other medical imaging modalities, including multi-modal image ...

Knowledge and experience with image review, annotation, and visual data analysis using image ... From medical, dental and vision benefits to generous paid time off (including a week-long company ...

Medical Image Annotation information

See Needham, MA salary details

$16

$40

$63

How much do medical image annotation jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for medical image annotation in Needham, MA is $40.63, according to ZipRecruiter salary data. Most workers in this role earn between $31.44 and $50.53 per hour, depending on experience, location, and employer.

What is medical image annotation?

Medical image annotation is the process of labeling or marking specific structures, regions, or abnormalities in medical images such as X-rays, CT scans, or MRIs. These annotations are crucial for training artificial intelligence (AI) models to assist in diagnostics, research, and treatment planning. Expert annotators, often with medical backgrounds, use specialized software to ensure accuracy and consistency. This work helps improve the performance of AI systems in identifying diseases and supporting healthcare professionals.

What are some common challenges faced by professionals in medical image annotation roles, and how can they be addressed?

Medical image annotation professionals often encounter challenges such as interpreting complex or ambiguous images, ensuring consistency across annotations, and keeping up with evolving medical guidelines. To address these challenges, many teams implement standardized protocols, regular training sessions, and peer review systems to maintain accuracy and reliability. Collaboration with radiologists and other medical experts is also common, allowing annotators to clarify uncertainties and improve the quality of annotations over time.

What is the difference between Medical Image Annotation vs Medical Data Labeling?

AspectMedical Image AnnotationMedical Data Labeling
Required CredentialsBasic understanding of medical imaging, attention to detailSimilar, often no formal certification needed
Work EnvironmentMedical imaging platforms, annotation toolsData management systems, labeling software
Industry UsageHealthcare, medical AI developmentHealthcare, medical AI, data analysis
Search & Comparison IntentYes, often compared for AI training rolesYes, related but broader in data types

Medical Image Annotation involves marking specific regions or features in medical images like X-rays or MRIs to train AI models. Medical Data Labeling encompasses annotating various medical data types, including images, text, and reports. While both roles support medical AI development, Image Annotation is specialized in visual data, whereas Data Labeling covers a wider range of medical information.

What are the key skills and qualifications needed to thrive as a Medical Image Annotation Specialist, and why are they important?

To excel as a Medical Image Annotation Specialist, you need a solid understanding of medical imaging modalities, anatomy, and basic clinical terminology, often supported by relevant education or experience in healthcare or life sciences. Familiarity with annotation software, image processing tools, and sometimes specialized platforms like DICOM viewers is typically required. Attention to detail, precision, and effective communication are crucial soft skills for ensuring accuracy and collaborating with clinical or research teams. These competencies are vital because high-quality, accurate annotations directly impact the development of AI models and the reliability of diagnostic tools in healthcare.
What job categories do people searching Medical Image Annotation jobs in Needham, MA look for? The top searched job categories for Medical Image Annotation jobs in Needham, MA are:
What cities near Needham, MA are hiring for Medical Image Annotation jobs? Cities near Needham, MA with the most Medical Image Annotation job openings:
Infographic showing various Medical Image Annotation job openings in Needham, MA as of July 2026, with employment types broken down into 70% Full Time, and 30% Part Time. Highlights an 100% In-person job distribution, with an average salary of $84,513 per year, or $40.6 per hour.
Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement

Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement

Harvard Medical Faculty Physicians

Boston, MA • On-site

Part-time

Medical, Dental, Vision, Life, Retirement

Posted 9 days ago


Job description

Job Description:
Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement, Part Time
Department of Pathology
Beth Israel Deaconess Medical Center
Harvard Medical School, Boston
The Department of Pathology at Beth Israel Deaconess Medical Center is seeking a Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement (Part-Time) faculty position (Boston).
As a teaching hospital of Harvard Medical School, BIDMC and the Department of Pathology, provide a clinically advanced and supportive academic environment for residents, fellows, and faculty. We're also proud and excited to be an integral part of the landmark collaboration among Dana-Farber Cancer Institute (DFCI), Beth Israel Deaconess Medical Center (BIDMC), and Harvard Medical Faculty Physicians (HMFP) to establish New England's only freestanding adult inpatient cancer hospital. The collaboration will provide unparalleled opportunities for pathologists and other physician specialties to be part of DFCI's internationally recognized cancer team.
The candidate will be appointed to the faculty of Harvard Medical School at a part-time academic rank (Lecturer, Instructor, Assistant Professor, Associate Professor) commensurate with experience.
Position Summary
Reporting to the Director of Digital Pathology (Primary), Department Chair or Vice Chair for Pathology Informatics, this faculty leadership role builds, scales, and operationalizes BIDMC Pathology's enterprise digital pathology ecosystem and serves as a department-wide expert for AI readiness, evaluation, and clinical deployment in anatomic pathology. The role partners closely with the Director of Digital Pathology key stakeholders (AP leadership, laboratory operations, IT and security, compliance, and research) to ensure safe, validated, high-quality digital workflows and an enduring education and mentorship program.
Key Responsibilities
Digital Pathology Infrastructure and Operations
Strategy and Roadmap
  • Lead a multi-year roadmap for whole slide imaging (WSI) and digital sign-out capabilities across BIDMC Pathology (clinical, educational, and research use cases). Define target-state architecture, phased milestones, resourcing, and success metrics.

Platform Build and Integration
  • Lead (or co-lead) selection, implementation, and lifecycle management for WSI scanners and a scanning operations model; the image management system and enterprise viewer; storage and archiving (on-premise and or cloud), networking, identity and access controls; and integration with LIS and EMR worklists and specimen tracking and barcoding workflows. Standardize SOPs across scanning, image QC, downtime procedures, and incident management.

Validation, Quality, and Compliance
  • Design and oversee validation protocols for primary diagnosis on digital slides (pathologist validation, case set design, discrepancy tracking, competency and re-validation cadence). Build a measurable QA and QC program for tissue-to-image fidelity (staining variability, scanner performance, display calibration, artefact classification, and remediation workflows). Ensure readiness for applicable regulatory and accreditation requirements (for example, CAP, CLIA, HIPAA, and institutional governance).

AI Enablement, Evaluation, and Clinical Deployment
AI Governance and Safety Framework
  • Establish an end-to-end governance model for AI tools used in pathology (selection, risk stratification, validation, monitoring, drift detection, versioning, change control, and retirement). Develop documentation standards and oversight pathways aligned with clinical risk, ethics, and equity principles.

AI readiness foundations
  • Build practical infrastructure to support AI translation, including dataset curation pipelines (de-identification, annotation frameworks, ground truth practices); a secure compute environment for evaluation and, where appropriate, model development; and performance benchmarking across representative case mixes and operational conditions.

Clinical implementation
  • Partner with clinical subspecialty leads to deploy AI tools into workflow (triage, screening support, quantification, QC augmentation), including user training, acceptance criteria, and post go-live monitoring.

Education program development and mentorship
Education program
  • Create and lead an ongoing "Digital Pathology and AI in Practice" education program for faculty pathologists and trainees; laboratory staff (histology, accessioning, scanning, and QC); and informatics and IT partners supporting pathology. Curriculum to include validation, workflow redesign, QC, human factors, AI evaluation literacy, and practical guidance on safe and responsible use of AI outputs.

Mentorship
  • Mentor trainees and faculty in digital pathology, computational pathology collaboration, and responsible AI adoption. Support scholarly output and career development for learners and junior faculty engaged in digital and AI initiatives.

Research, innovation, and external collaboration
  • Enable clinical-translational research through high-quality digital slide repositories and standardized data capture. Support grants, publications, and multi-institution collaborations related to digital pathology, AI evaluation, and implementation science. Develop and manage academically appropriate industry collaborations (evaluations, pilots, interoperability work), aligned with BIDMC policies.

Qualifications
  • MD or DO with board certification in Anatomic Pathology (or AP/CP).

  • Eligibility for medical licensure in Massachusetts.

  • Demonstrated expertise in computational pathology, pathology informatics, image analysis, artificial intelligence, or related domains.

  • Experience leading multidisciplinary programs or initiatives involving clinical, computational, and informatics teams.

  • Knowledge of regulatory and quality frameworks for digital and computational pathology systems.

  • Track record of scholarly activity, innovation, or program development in computational pathology or informatics.

  • Strong communication and change management skills.

Preferred Attributes
  • Visionary leader capable of advancing data-driven transformation in pathology at institutional and national levels.

  • Dual fluency in medicine and computing or informatics, with a portfolio spanning clinical pathology practice plus technical infrastructure development.

  • Strong ability to collaborate across clinical, research, engineering, and informatics domains.

  • Commitment to clinical excellence, innovation, and academic scholarship.

  • Interest in contributing to national and international initiatives shaping the future of computational pathology.

Beth Israel Deaconess Medical Center, a 743-bed hospital and Level 1 Trauma Center, is a founding member of Beth Israel Lahey Health (BILH). BILH, a health care system with 14 hospitals, brings together academic medical centers and teaching hospitals, community and specialty hospitals, and more than 4,000 physicians and 39,000 employees in a shared mission to expand access and advance the science and practice of medicine through groundbreaking research and education.
Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center (HMFP) is one of the largest physician organizations in New England, dedicated to excellence and innovation in patient care, education, and research. As a physician-led organization, HMFP partners with more than 2,400 providers to support the delivery of exceptional care, promote professional development, and foster balance at work and home. HMFP physicians have faculty affiliations with Harvard Medical School (HMS) and provide care throughout the BILH system and additional hospitals across Massachusetts.
Research
Beth Israel Deaconess Medical Center consistently ranks as a national leader among independent hospitals in National Institutes of Health funding. Research funding totals over $229.8 million annually. BIDMC researchers run more than 850 active sponsored projects and 500 funded and non-funded clinical trials.
The Harvard-Thorndike Laboratory, the nation's oldest clinical research laboratory, has been located on this site since 1973. BIDMC also shares important clinical and research programs with institutions such as the Dana-Farber/Harvard Cancer Center, Joslin Diabetes Center and Children's Hospital.
For information about the position, please contact Dr. Monika Vyas (mvyas1@bidmc.harvard.edu). Candidates should apply directly online at www.hmfphysicians.org/careers. Requisition Number: R1619
Pay Range:
$269,000 - $321,000
The base pay range reflects what Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center (HMFP) reasonably and in good faith expects to pay for this role at the time of posting and may be modified from time to time. Actual compensation within this range may be determined based on several factors, including academic appointment, work experience, specialty training, geography of work location, anticipated productivity, FTE basis, and role expectations. In addition to base compensation, this role may be eligible for performance-based incentives, which may include bonuses for productivity and quality HMFP also offers a comprehensive and generous employee benefits program to eligible employees, including health, dental, vision, life, and disability insurance, as well as retirement plan(s) with employer contributions.