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Data Annotation Jobs in Memphis, TN (NOW HIRING)

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Data Annotation information

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What are the most commonly searched types of Data Annotation jobs in Memphis, TN? The most popular types of Data Annotation jobs in Memphis, TN are:
What are popular job titles related to Data Annotation jobs in Memphis, TN? For Data Annotation jobs in Memphis, TN, the most frequently searched job titles are:
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Infographic showing various Data Annotation job openings in Memphis, TN as of July 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 26% Part Time, 2% Contract, 35% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.

Staff Software Engineer / Machine Learning Engineer - Radiology

St. Jude Children's Research Hospital

Memphis, TN • On-site

Full-time

Re-posted 2 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 1,054 rated hospitals


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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