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Staff Software Engineer / Machine Learning Engineer - RadiologyNature Careers • United States
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Staff Software Engineer / Machine Learning Engineer - Radiology

Nature Careers
  • US
    United States
  • US
    United States
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À propos

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.
  • United States

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  • English
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