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Machine Learning Engineer Associate Jobs in Tennessee

Senior Data Engineer

Memphis, TN · On-site

$103K - $139K/yr

Azure Data Engineer Associate . * Hands-on experience with Azure Data Factory, Azure Synapse, Azure Data Lake, and Power BI . * Knowledge of machine learning models and data science techniques in a ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Production Engineer Associate

Clarksville, TN · On-site

$63K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The Production Engineering Associate will be tasked with duties including, but not limited to ... Knowledge of Computer or Machine Learning Techniques to build models * Excellent communication ...

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 ...

Showing results 41-60

Machine Learning Engineer Associate information

What is a machine learning engineer associate?

Machine Learning Engineer Associates are entry-level professionals who help design, build, and maintain machine learning models and systems. They typically work under the guidance of senior engineers, assisting in data preprocessing, model training, and testing. Their responsibilities may include implementing algorithms, evaluating model performance, and deploying solutions to production environments. This role requires a strong foundation in programming, statistics, and machine learning principles, often acquired through education or internships.

What are some common challenges faced by machine learning engineer associates when deploying models to production?

Machine Learning Engineer Associates often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and addressing issues with model drift after deployment. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, balancing model performance with resource constraints and maintaining clear documentation for reproducibility are important aspects of the role. Gaining familiarity with deployment tools and best practices can help overcome these hurdles.

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

To thrive as a Machine Learning Engineer Associate, you need a solid understanding of programming (especially Python), mathematics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with version control systems such as Git are essential. Strong problem-solving abilities, communication skills, and a collaborative mindset help you work effectively within technical teams. These competencies ensure you can develop, implement, and improve machine learning models that deliver actionable insights and drive business value.

What are the most commonly searched types of Machine Learning Engineer jobs in Tennessee?

The most popular types of Machine Learning Engineer jobs in Tennessee are:

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

Cities in Tennessee with the most Machine Learning Engineer Associate 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 12 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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