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Senior Medical Annotation Jobs (NOW HIRING)

Simbe Robotics, Inc.

$160 - $200/hr

You will work on the full model lifecycle: data, annotation quality, training, evaluation, release ... medical, financial, and other benefits. Details of participation in these benefit plans will be ...

Abbott

Senior Staff AI/ML Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Our medical devices help more than 10,000 people have healthier hearts, improve quality of life for ... Work on end-to-end ML solutions development and delivery, including data ingestion, annotation ...

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Our medical devices help more than 10,000 people have healthier hearts, improve quality of life for ... ingestion,annotation,feature engineering, training, validation, deployment, and monitoring.

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Our medical devices help more than 10,000 people have healthier hearts, improve quality of life for ... ingestion,annotation,feature engineering, training, validation, deployment, and monitoring.

Verantos

Senior Product Manager

$129K - $170K/yr

... HEOR, medical affairs, and regulatory use. Our product strategy is built on three modular ... Partner with the users and cross-functional collaborators - annotators, annotation supervisors ...

Verantos

Senior Product Manager

$129K - $170K/yr

... HEOR, medical affairs, and regulatory use. Our product strategy is built on three modular ... Partner with the users and cross-functional collaborators - annotators, annotation supervisors ...

Coalition, Inc.

WV

$200K/yr

Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program ... Perks * 100% medical, dental and vision coverage * Flexible PTO policy * Annual home office stipend ...

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Senior Medical Annotation information

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$25K

$80.3K

$163.5K

How much do senior medical annotation jobs pay per year?

As of Sep 4, 2026, the average yearly pay for senior medical annotation in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What is a senior medical annotation?

Senior Medical Annotation specialists are experienced professionals who review and label medical data, such as clinical notes, images, or audio, to ensure it is accurately structured for use in research, artificial intelligence, or healthcare analytics. They have in-depth knowledge of medical terminology and guidelines, allowing them to provide high-quality, consistent annotations. Their work is critical in training and validating AI models for tasks like disease detection or medical record organization. Senior specialists often lead annotation teams, provide quality control, and help develop annotation protocols.

What are the key skills and qualifications needed to thrive as a senior medical annotation specialist?

To thrive as a Senior Medical Annotation Specialist, you need in-depth knowledge of medical terminology, clinical guidelines, and experience with healthcare data, usually supported by a degree in a life science or healthcare field. Familiarity with annotation tools, electronic health records (EHR) systems, and data labeling platforms is typically required, along with certifications in medical coding or informatics. Strong attention to detail, analytical thinking, and effective communication are crucial soft skills for quality assurance and teamwork. These skills ensure the accuracy and reliability of annotated medical data, which is essential for healthcare research, AI development, and clinical decision-making.

What are some common challenges faced by senior medical annotation professionals, and how can they be managed?

Senior Medical Annotation professionals often encounter challenges such as handling large volumes of complex medical data, maintaining accuracy under tight deadlines, and keeping up with evolving medical terminologies. Managing these challenges requires strong attention to detail, effective use of annotation tools, and ongoing communication with clinical experts and data scientists. Continuous learning and collaboration within multidisciplinary teams help ensure high-quality outputs and foster professional growth within the field.

What is the difference between Senior Medical Annotation vs Medical Data Labeler?

AspectSenior Medical AnnotationMedical Data Labeler
CredentialsTypically requires healthcare background, medical terminology knowledge, and experience with annotation toolsOften requires basic computer skills, training in data labeling, but less healthcare-specific knowledge
Work EnvironmentRemote or on-site, working with complex medical datasets and annotation softwarePrimarily remote, focusing on labeling large volumes of medical images or text
Industry UsageUsed in AI development for healthcare, medical research, and clinical data projectsUsed in machine learning datasets creation, quality control, and data preparation

Senior Medical Annotation professionals typically have healthcare experience and handle complex annotations, while Medical Data Labelers focus on large-scale data labeling tasks with less healthcare-specific expertise. Both roles are essential in AI healthcare projects but differ in complexity and required background.

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What cities are hiring for Senior Medical Annotation jobs?

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What are the most commonly searched types of Medical Annotation jobs?

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What states have the most Senior Medical Annotation jobs?

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Senior Medical Annotation jobs near you
Infographic showing various Senior Medical Annotation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.

Senior Computer Vision / Applied AI Engineer

Simbe Robotics

San Francisco, CA • On-site

$160K - $200K/yr

Full-time

Re-posted 18 hours ago

Job description

Simbe is building the AI powered operating system for physical retail. Our autonomous robots and multimodal computer vision platform turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and customer focused product design to help retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity.

Simbe is looking for a Senior Computer Vision / Applied AI Engineer to build production AI systems that turn store imagery into trusted retail intelligence. This role will work across dense product detection, price tag and promo tag detection, OCR, barcode decoding, product association, segmentation, visual search, model evaluation, and customer specific model improvements. The right person isa strong ML engineer, an exceptional software engineer, and a practical builder who enjoys messy real world data, rapid iteration, and measurable customer impact.

Why This Role Is High Impact
  • You will work on dense, cluttered, real world visual scenes where accuracy directly drives customer value.
  • You will help improve core Simbe use cases such as out of stock detection, price accuracy, promo compliance, top stock, and product location intelligence.
  • You will work on the full model lifecycle: data, annotation quality, training, evaluation, release, monitoring, and production debugging.
Responsibilities
  • Build production CV models. Design, train, validate, and deploy models for object detection, segmentation, OCR, barcode localization, product recognition, shelf understanding, and other customer facing computer vision tasks.
  • Own dataset quality. Curate, clean, version, and analyze large real world training datasets, including hard negative mining, annotation QA, data audits, and active learning workflows.
  • Improve model performance. Research and implement model architecture, loss function, data augmentation, synthetic data, and evaluation improvements that increase precision, recall, latency, and robustness across customers.
  • Support model releases. Contribute to model validation, release gates, inference wrappers, ONNX/TensorRT exports, and production monitoring so models are reliable in customer environments.
  • Develop tooling. Build internal tools for model evaluation, annotation review, error mining, data visualization, dataset exports, and deployment readiness.
  • Partner cross functionally. Work closely with Product, Customer Success, Data, Robotics Software, and Field Operations to turn customer issues into model and pipeline improvements.
  • Stay current. Track modern work in open vocabulary detection, promptable segmentation, multimodal product understanding, visual search, OCR, and edge inference, and evaluate where it can create value for Simbe.
Required Qualifications
  • 5+ years of experience in computer vision, applied machine learning, robotics perception, or related production AI systems.
  • Strong Python experience and hands on experience with PyTorch or TensorFlow.
  • Demonstrated experience using AI-assisted coding and automation tools to accelerate software development, debugging, experimentation, and engineering workflows, with strong judgment around validating and reviewing AI-generated output.
  • Experience training and evaluating object detection, segmentation, OCR, visual search, or image recognition models.
    Strong understanding of dataset curation, annotation quality, model evaluation, error analysis, and experimentation.
  • Experience building maintainable production code and data pipelines in a Linux based environment.
  • Ability to balance research quality with production constraints such as latency, compute, memory, robustness, and ease of deployment.
  • Strong communication skills and a customer value mindset.
Bonus Qualifications
  • Experience with retail, product recognition, shelf intelligence, OCR, barcode decoding, fine grained recognition, or visual product search.
  • Experience with ONNX, TensorRT, CUDA, quantization, model profiling, or edge deployment.
  • Experience with C++, ROS/ROS2, RGBD cameras, 3D geometry, homography, calibration, or robotic perception.
  • Experience with FiftyOne, CVAT, Labelbox, Roboflow, or other data centric ML tools.
  • Experience with synthetic data generation, simulation, active learning, or automated annotation workflows.
  • Publications, patents, open source contributions, or production systems in relevant CV/AI domains.
$160,000 - $200,000 a year

The base salary offered is based on market location and may vary depending on individualized factors for job candidates, including job related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include equity compensation, in addition to a full range of medical, financial, and other benefits. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

Simbe Values: R. E. T. A. I. L.

  • Result Driven - We are customer centric and results driven. We strive to create immense value for our team, partners, customers, and investors.

  • Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally.

  • Transparent - We value open communication internally, and with our partners and customers. We are receptive to feedback.

  • Agile - We are eager to learn and adapt quickly to changes and customer needs.

  • Innovative - We are bold and innovative, with an intense focus on product design, user experience, and customer value.

  • Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field.

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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