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Commission Medical Data Annotation Jobs in Tennessee

... medical microbiology. * Assess the impact of antibiotics and other agents on microbial populations ... Document experimental findings and processes with a focus on clarity for AI training data.

... medical microbiology. * Assess the impact of antibiotics and other agents on microbial populations ... Document experimental findings and processes with a focus on clarity for AI training data.

... medical microbiology. * Assess the impact of antibiotics and other agents on microbial populations ... Document experimental findings and processes with a focus on clarity for AI training data.

Medical Support Assistant

Savannah, TN · On-site

$31K - $40K/yr

Performs clerical and administrative functions to maintain patient data. * Schedules new and ... Complies with all federal, state, local, Joint Commission, Occupational Safety and Health ...

Showing results 21-40

Commission Medical Data Annotation information

What are some common challenges faced in a commission medical data annotation role and how can they be addressed?

In a Commission Medical Data Annotation role, professionals often encounter challenges such as interpreting complex medical terminology, ensuring consistency in labeling, and maintaining high accuracy under tight deadlines. To address these, it is helpful to regularly reference standardized guidelines, participate in team reviews or audits, and seek clarification from medical experts when needed. Collaborating with peers and utilizing annotation tools efficiently can also help streamline the process and minimize errors, ensuring both quality and productivity.

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

AspectCommission Medical Data AnnotationMedical Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or office-based, tech-focusedRemote or office-based, tech-focused
Industry UsageUsed in AI training for healthcare applicationsUsed in AI training for healthcare applications
Search IntentComparison of roles in medical data annotationComparison of roles in medical data annotation

Both roles involve labeling medical data to train AI systems, often requiring similar skills and work environments. The main difference lies in the scope: Commission Medical Data Annotation may involve more specialized tasks or higher-level responsibilities, whereas Medical Data Labeler typically refers to the basic task of data labeling. Understanding these distinctions helps job seekers identify roles aligned with their skills and career goals.

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

To thrive as a Commission Medical Data Annotation Specialist, you need a solid understanding of medical terminology, data annotation techniques, and attention to detail, often with a background in life sciences or healthcare. Familiarity with annotation platforms, data labeling tools, and compliance standards such as HIPAA is typically required. Strong analytical skills, meticulousness, and effective communication make someone stand out in this position. These skills are crucial for ensuring high-quality, accurate data that supports reliable AI and research outcomes in medical applications.

What is a commission medical data annotation?

Commission medical data annotation jobs involve labeling and categorizing medical data—such as images, clinical notes, or audio recordings—for use in training machine learning models in healthcare. Workers are typically paid based on the amount of data they accurately annotate, rather than an hourly wage. Tasks may include identifying diseases in medical images, transcribing doctor notes, or classifying medical records. These jobs are critical for developing reliable artificial intelligence systems in medicine, supporting applications like diagnostics, treatment planning, and research. Attention to detail, understanding of medical terminology, and adherence to privacy standards are essential in these roles.
What are the most commonly searched types of Medical Data Annotation jobs in Tennessee? The most popular types of Medical Data Annotation jobs in Tennessee are:
What are popular job titles related to Commission Medical Data Annotation jobs in Tennessee? For Commission Medical Data Annotation jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Commission Medical Data Annotation jobs in Tennessee look for? The top searched job categories for Commission Medical Data Annotation jobs in Tennessee are:
What cities in Tennessee are hiring for Commission Medical Data Annotation jobs? Cities in Tennessee with the most Commission Medical Data Annotation job openings:
Infographic showing various Commission Medical Data Annotation job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Staff Software Engineer / Machine Learning Engineer - Radiology

St. Jude Children's Research Hospital

Memphis, TN • On-site

$104 - $186.16/hr

Other

Re-posted 4 days ago


St. Jude Children's Research Hospital rating

8.6

Company rating: 8.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

40th of 1,055 rated hospitals


Job description

Location

Memphis, TN

Category

Computational Sciences

Department

Radiology

Shift

Weekday Day

Position Type

Full Time

Scheduled Weekly Hours

40

JR7176

Job Description

We are seeking a highly motivated and experienced Machine Learning Engineer to develop advanced machine learning (ML), deep learning (DL), and foundational AI models for medical imaging. This role focuses on building robust algorithms for segmentation, quantification, and detection across CT, MRI, and X‑ray. This position sits at the center of a well‑resourced, data‑rich research environment with established infrastructure for multi‑institutional data aggregation, curation, and large‑scale annotation. St. Jude Children’s Hospital has incredible high‑performance computing resources. The lab leverages curated datasets from diverse sources, dedicated annotation teams, and external engineering support, enabling this role to focus on high‑impact model development, validation, and clinical translation. Many projects are designed with a path toward regulatory clearance via FDA’s 510(k) or De Novo pathways, and the successful candidate will work closely with regulatory and quality experts to support reproducible, well‑documented, and clinically deployable AI solutions. This role offers a unique combination of academic productivity (authorship opportunities) and real‑world impact through translation into clinical practice.

Machine Learning Engineer

Key Responsibilities

  • Develop, train, and validate state‑of‑the‑art ML/DL models for segmentation, quantification, and detection across CT, MRI, and X‑ray
  • Design and implement 2D and 3D model architectures (CNNs, transformer‑based, and foundational models)
  • Build scalable pipelines for data preprocessing, model training, evaluation, and deployment
  • Develop quantitative imaging methods (e.g., volumetrics, density measurements, biomarker extraction)
  • Leverage curated, multi‑institutional datasets to ensure model generalizability and robustness
  • Collaborate with radiologists and engineering teams to define clinically meaningful outputs
  • Produce regulatory‑grade documentation for datasets, model development, validation, and performance
  • Ensure reproducibility and traceability of experiments (data, model, and code versioning)
  • Work collaboratively with regulatory and quality experts to support FDA 510(k) and De Novo submissions, including providing technical documentation and validation evidence
  • Contribute to software quality and security practices, including supporting activities such as vulnerability assessment and penetration testing in collaboration with cybersecurity and regulatory teams
  • Utilize modern AI‑assisted development tools (e.g., LLM‑based coding agents) to accelerate development and improve code quality
  • Participate in team‑based development practices (code reviews, Git, testing frameworks)
  • Support manuscripts, grants, and technical reporting

Minimum Education and/or Training:

  • Bachelor’s degree in computer science, data science, information science, business, or related field.
  • Master’s degree preferred.

Minimum Experience:

  • Minimum Requirement: Bachelor’s degree with 5+ years of experience required.
  • Experience Exception: Master’s degree with 3+ years of experience.
  • Experience with programming languages, databases, and software development lifecycle
  • Experience with the position‑specific technical stack preferred
  • Experience with the position‑specific scientific domain preferred
  • Proven performance in earlier role/comparable role

Preferred Qualifications

  • 3+ years of experience developing ML/DL models for image analysis
  • Demonstrated experience with segmentation, detection, and/or quantitative imaging algorithms (2D and/or 3D)
  • Strong proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Experience with modern architectures (U‑Net variants, detection frameworks, transformers, or foundational models)
  • Familiarity with DICOM and medical imaging workflows
  • Strong understanding of evaluation metrics (Dice, IoU, ROC/AUC, sensitivity/specificity)
  • Experience with version control and collaborative development (e.g., Git)
  • Demonstrated ability to produce clear, structured technical documentation
  • Experience using modern LLM‑based coding assistants (e.g., Claude, Codex, or similar) to enhance development workflows
  • (Strongly preferred) Experience developing and documenting AI solutions for clinical translation or regulatory submission (e.g., FDA 510(k))
  • Familiarity with Good Machine Learning Practice (GMLP)
  • Experience collaborating with regulatory, quality, or cybersecurity teams
  • Exposure to software security principles (e.g., secure coding, vulnerability assessment, penetration testing concepts)
  • Experience with large, multi‑institutional datasets
  • Familiarity with radiology workflows and quantitative imaging biomarkers
  • Experience with cloud or high‑performance computing environments
  • Experience deploying models into research or clinical environments

Academic and Career Development Opportunities

  • Significant opportunities for authorship on high‑impact manuscripts
  • Active participation in multi‑institutional research collaborations
  • Opportunities to contribute to grant proposals and funded research initiatives
  • Exposure to translational AI development, including projects targeting FDA 510(k) clearance
  • Ability to build a strong academic portfolio in parallel with real‑world clinical impact

Key Attributes

  • Highly collaborative and team‑oriented
  • Detail‑oriented with strong commitment to documentation, reproducibility, and auditability
  • Able to operate effectively in a translational, regulatory‑aware environment
  • Strong interest in delivering clinically impactful AI solutions

Compensation

In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate offered in good faith and a specific salary offer takes into account factors that are considered in making compensation decisions including but not limited to skill sets, experience and training, licensure and certifications, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the salary range and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current salary range is $104,000 - $186,160 per year for the role of Staff Software Engineer / Machine Learning Engineer - Radiology.

Explore our exceptional benefits !

St. Jude is an Equal Opportunity Employer

No Search Firms

St. Jude Children’s Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

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