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Deep Learning Ai Jobs in Michigan (NOW HIRING)

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

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Showing results 1-20

Deep Learning Ai information

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What cities in Michigan are hiring for Deep Learning Ai jobs?

Cities in Michigan with the most Deep Learning Ai job openings:

Infographic showing various Deep Learning Ai job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Data Scientist - AI and ECG

University Of Michigan

Ann Arbor, MI • On-site

$110 - $150/hr

Other

Medical, Dental, Vision, Retirement

Posted 21 days ago


University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

167th of 621 rated colleges and universities


Job description

Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally.Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

Job Summary

The Division of Cardiovascular Medicine at the University of Michigan is expanding a nationally and internationally funded research program at the cutting edge of cardiovascular medicine. Led by Drs. Venkatesh Murthy and Sascha Goonewardena - whose work has appeared in leading journals including NEJM AI, JAMA, and Circulation - the program fuses artificial intelligence, advanced cardiac imaging, multiomics (proteomics, metabolomics, and genomics), and cardiometabolic disease biology to develop precision diagnostics and identify novel therapeutic approaches, with a particular focus on coronary microvascular disease and other cardiovascular conditions that disproportionately affect women and remain poorly served by existing diagnostic tools. This is a rare opportunity to join a high-impact, well-funded program doing science that matters.

This position serves as the primary AI and ECG computational scientist for the program. The incumbent will build and train deep learning foundation models and drive the computational work that connects cardiac electrical signatures to biological disease mechanisms. This is an engineering and infrastructure-focused role; the incumbent builds and optimizes the models and data systems that power the program's AI-driven analyses. This is one of two senior data scientist roles; the two positions serve complementary, non-overlapping functions.

Responsibilities*
  • Develop, train, and refine deep learning foundation models (including transformer and self-supervised architectures) for ECG-based detection and endotyping of cardiometabolic disease
  • Assemble, harmonize, clean, and catalog large-scale, heterogeneous ECG datasets from multiple internal and external sources and formats
  • Build and maintain reproducible data processing pipelines, data loaders, and PostgreSQL-based data management infrastructure
  • Evaluate model performance, document methods, and prepare written and code-based analytical reports (Python)
  • Contribute to manuscripts, grant reports, and presentations
  • Collaborate with collaborative network partners and other research collaborators on code, computational workflows, and data harmonization
  • Other duties as assigned
Required Qualifications*
  • Masters or doctoral degree in computer science, electrical engineering, biomedical engineering, computational biology, statistics with an AI/ML focus, data science, or a closely related quantitative field
  • Demonstrated experience developing and training deep learning models, preferably in a biomedical or physiological signal context
  • Proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable)
  • Experience with large-scale, heterogeneous data harmonization and processing pipelines spanning multiple source formats
  • Familiarity with self-supervised, semi-supervised, or foundation model architectures (e.g., transformers, masked autoencoders)
  • Proficiency in SQL, preferably PostgreSQL, for data querying and management
  • Experience with high-performance computing environments, including Slurm-based job scheduling
  • Strong organizational skills and attention to detail
  • Ability to prepare and present written and code-based (Python or R) analytical reports
  • Strong scientific communication skills; ability to contribute to manuscripts and grant reports
Desired Qualifications*
  • Experience with electrocardiographic (ECG) or other physiological waveform data
  • Experience with multimodal data integration, particularly combining physiological signals with cardiac imaging data
  • Familiarity with clinical data infrastructure (EHR, DICOM, HL7/FHIR)
  • Experience with transfer learning or domain adaptation across heterogeneous datasets
  • Track record of peer-reviewed publications or preprints in machine learning, AI, or biomedical informatics
  • Familiarity with cardiovascular physiology or cardiology research
  • Experience with Git and reproducible research practices
  • Familiarity with cloud computing environments (AWS, GCP, or Azure)
Why Join Michigan Medicine?

Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world?s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.

What Benefits can you Look Forward to?

  • Excellent medical, dental and vision coverage effective on your very first day
  • 2:1 Match on retirement savings
Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .

Work Schedule

Work Schedule: Monday through Friday, standard business hours. This is an onsite position.

Additional Information

We, the staff and faculty of the U-M Cardiovascular Center (CVC) team, are committed to advancing medicine and serving humanity through living and teaching our core values of Respect and Compassion; Collaboration; Innovation; and Commitment to Excellence. Each CVC employee is expected to understand and demonstrate that in every interaction we represent our entire organization in the care we provide and in the courtesies we extend to patients, families, and each respective team member. The CVC is dedicated to partnering with patients and families to deliver the safest and highest quality of health care.

The Division of Cardiovascular Medicine is firmly committed to advancing inclusion, diversity, equity, accessibility, and belonging, which are core to the culture and values of the Medical School Office of Research. Our community supports recruiting and cultivating a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan and the world. We strive to create a work culture where each team member feels respected, valued, and safe.

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Application Deadline

Job openings are posted for a minimum of seven calendar days.The review and selection process maybegin as early as the eighth day after posting.Thisopening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.

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About University of Michigan

Sourced by ZipRecruiter

The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

Year founded

1817

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