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Machine Learning Engineer Apprenticeship Jobs in Tennessee

Machine Learning Tutor

Memphis, TN · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machinist Apprentice

Cookeville, TN · On-site

$15.25 - $19.50/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... basic machine care activities.Work collaboratively with machinists, engineers, and fabrication ... Demonstrate a commitment to continuous learning and skill development throughout the apprenticeship ...

Showing results 41-60

Machine Learning Engineer Apprenticeship information

What is a machine learning engineer apprenticeship?

A Machine Learning Engineer Apprenticeship is a structured training program that combines hands-on work experience with classroom or online learning in the field of machine learning. Apprentices work under the guidance of experienced professionals to develop skills in data analysis, building machine learning models, and deploying algorithms in real-world applications. This apprenticeship is ideal for individuals seeking to enter the field of artificial intelligence without prior extensive experience, as it provides practical training and mentorship. Typically, apprenticeships last from several months to a couple of years and may lead to full-time employment upon successful completion.

What types of projects can I expect to work on during a machine learning engineer apprenticeship?

As a Machine Learning Engineer Apprentice, you can expect to participate in hands-on projects that involve data preprocessing, building and evaluating machine learning models, and collaborating with cross-functional teams such as data scientists and software engineers. Common projects may include developing recommendation systems, automating data analysis tasks, or implementing natural language processing solutions. These experiences provide valuable exposure to real-world datasets and industry-standard tools, helping you build foundational skills for a long-term career in machine learning.

What are the key skills and qualifications needed to thrive as a machine learning engineer apprentice, and why are they important?

To thrive as a Machine Learning Engineer Apprentice, a solid understanding of mathematics, programming (especially Python), and foundational machine learning concepts is essential, often supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically required. Strong analytical thinking, attention to detail, and the ability to collaborate and communicate complex ideas clearly are valuable soft skills. These abilities are crucial for efficiently developing, testing, and deploying machine learning models while contributing effectively to team projects.

What are popular job titles related to Machine Learning Engineer Apprenticeship jobs in Tennessee?

For Machine Learning Engineer Apprenticeship jobs in Tennessee, the most frequently searched job titles are:

What cities in Tennessee are hiring for Machine Learning Engineer Apprenticeship jobs?

Cities in Tennessee with the most Machine Learning Engineer Apprenticeship job openings:

Staff Software Engineer / Machine Learning Engineer - Radiology

St. Jude Children's Research Hospital, Inc.

Memphis, TN • On-site

$104 - $186.16/hr

Other

Re-posted 13 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

43rd of 1,060 rated hospitals


Job description

Machine Learning Engineer

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.

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, and the 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
  • Ability 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!

Equal Opportunity Employer

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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