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Deep Learning Data Scientist II

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting

What you’ll work on

Full posting

We are seeking a motivated Data Scientist to research, develop, and enhance AI/ML algorithms for computer vision and healthcare applications.

Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision applications, translating advances in AI research into practical healthcare solutions.

  • Research, develop, and evaluate deep learning algorithms for computer vision in healthcare

  • Build and optimize model deployment pipelines for efficient, scalable inference

  • Apply model optimization techniques while keeping accuracy high

  • Maintain data quality and integrity across the data lifecycle

  • Work with clinical partners to translate needs into AI/ML solutions

From the employer’s posting
We are seeking a motivated Data Scientist to research, develop, and enhance AI/ML algorithms for computer vision and healthcare applications. This role involves developing and improving deep learning models, maintaining high standards of data quality, optimizing models for efficient deployment, and translating advances in AI research into practical healthcare solutions. The Data Scientist will collaborate with clinical partners and internal stakeholders to understand clinical and business needs and develop appropriate technical solutions. The ideal candidate will be capable of independently managing research and development projects while contributing effectively within cross-functional teams. Success in this role requires strong technical and communication skills, attention to detail, persistence, and a commitment to staying current with advances in AI/ML and computer vision.
Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision applications, translating advances in AI research into practical healthcare solutions.
Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision applications
Implement and optimize model deployment pipelines to enable efficient, scalable, and hardware-optimized inference.
Apply model optimization techniques to improve computational efficiency and inference performance while maintaining model accuracy.
Maintain data quality and integrity throughout the data lifecycle
Collaborate with clinical partners and internal stakeholders to understand clinical and business needs and translate them into appropriate AI/ML solutions.

What you’ll bring

All qualifications

Core experience

  • Knowledge, Skills, and Abilities:
  • Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow.
  • Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.
  • Solid understanding of model optimization techniques, including pruning, quantization, mixed-precision inference, and other strategies for improving computational efficiency and inference performance.

Preferred experience

  • Experience working with multispectral and/or hyperspectral imaging data.
  • Experience with generative AI models for medical image synthesis and simulation.
  • Experience applying AI/ML methodologies to healthcare or biomedical applications, with demonstrated contributions to successful research, clinical, or product outcomes.
Qualification wording
Knowledge, Skills, and Abilities:
Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow.
Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.
Solid understanding of model optimization techniques, including pruning, quantization, mixed-precision inference, and other strategies for improving computational efficiency and inference performance.
Experience working with multispectral and/or hyperspectral imaging data.
Experience with generative AI models for medical image synthesis and simulation.
Experience applying AI/ML methodologies to healthcare or biomedical applications, with demonstrated contributions to successful research, clinical, or product outcomes.
Education & alternatives
Qualifications: - M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative field. - Minimum of two years of relevant research or professional experience in computer vision. For candidates with a master’s degree, the required experience must be professional experience obtained after completion of the degree.
- M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative field. - Minimum of two years of relevant research or professional experience in computer vision. For candidates with a master’s degree, the required experience must be professional experience obtained after completion of the degree. Knowledge, Skills, and Abilities:
Apply at Spectral AI

Posting record

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Status in our records
Live
First seen by us
Sep 22, 202644 days ago
Recorded sightings
27
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 44

Similar jobs usually come down between day 7 and day 56.

From 10,194 similar postings that came down. Coming down is not always a hire.

Spectral AI is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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  • Python
  • PyTorch
  • TensorFlow
Where the posting names them
Knowledge, Skills, and Abilities: - Strong programming skills in Python and experience developing maintainable, reproducible code for machine learning applications. - Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation.
- Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation. - Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow. - Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.

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About Spectral AI

People
About 65 in 2025, down 17% from the year before.Annual report (SEC Form 10-K)
Company
Listed as MDAI.

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Position Summary: 

 

We are seeking a motivated Data Scientist to research, develop, and enhance AI/ML algorithms for computer vision and healthcare applications. This role involves developing and improving deep learning models, maintaining high standards of data quality, optimizing models for efficient deployment, and translating advances in AI research into practical healthcare solutions. The Data Scientist will collaborate with clinical partners and internal stakeholders to understand clinical and business needs and develop appropriate technical solutions. The ideal candidate will be capable of independently managing research and development projects while contributing effectively within cross-functional teams. Success in this role requires strong technical and communication skills, attention to detail, persistence, and a commitment to staying current with advances in AI/ML and computer vision.

 

Essential Duties and Responsibilities:

 

  • Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision applications, translating advances in AI research into practical healthcare solutions.
  • Implement and optimize model deployment pipelines to enable efficient, scalable, and hardware-optimized inference.
  • Apply model optimization techniques to improve computational efficiency and inference performance while maintaining model accuracy.
  • Maintain data quality and integrity throughout the data lifecycle to support robust algorithm development, training, and evaluation.
  • Collaborate with clinical partners and internal stakeholders to understand clinical and business needs and translate them into appropriate AI/ML solutions.
  • Independently manage assigned research and development projects from problem formulation through implementation, evaluation, and delivery.
  • Ensure reproducibility of analyses and experiments through clear documentation, version-controlled workflows, and effective knowledge sharing.
  • Stay current with advances in AI/ML, computer vision, and related technologies and evaluate their applicability to ongoing research and development.
  • Communicate technical methods, results, and recommendations effectively to both technical and non-technical stakeholders.


Qualifications:

 

  • M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative field.
  • Minimum of two years of relevant research or professional experience in computer vision. For candidates with a master’s degree, the required experience must be professional experience obtained after completion of the degree. 


Knowledge, Skills, and Abilities:


  • Strong programming skills in Python and experience developing maintainable, reproducible code for machine learning applications.
  • Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation.
  • Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow.
  • Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.
  • Solid understanding of model optimization techniques, including pruning, quantization, mixed-precision inference, and other strategies for improving computational efficiency and inference performance.
  • Working knowledge of model deployment and inference tools, such as ONNX, LibTorch, and TensorRT.
  • Self-driven and capable of independently navigating ambiguous research problems, working with incomplete data, and delivering high-quality results.
  • Strong written and verbal communication skills, including the ability to prepare technical documentation, reports, and scientific manuscripts.


Preferred Qualifications:

 

  • Experience working with multispectral and/or hyperspectral imaging data.
  • Experience with generative AI models for medical image synthesis and simulation.
  • Experience applying AI/ML methodologies to healthcare or biomedical applications, with demonstrated contributions to successful research, clinical, or product outcomes.


Physical Requirements:

 

Prolonged periods of sitting at a desk and working on a computer.


Travel:

 

N/A


Equal Employment Opportunity:

 

Spectral MD, Inc. is an equal opportunity and affirmative action employer. All applicants will be considered for employment without regard to race, color, ancestry, national origin, sex, gender, sexual orientation, marital status, religion, age, disability, gender identity, results of genetic testing, protected veteran status, or any other characteristic protected by applicable federal, state or local laws.


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Dallas, TX, US

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