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Multimodal Learning Jobs in Minnesota (NOW HIRING)

Autodesk

Job Requisition ID # 26WD97132 26WD97132, Pr incipal Machine Learning Engineer, ML Platform and ... Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data

OATI

AI Engineer

Bloomington, MN

$100K - $150K/yr

Design, build and fine-tune large foundation AI models (e.g., LLMs, multimodal models) for the ... Develop and implement machine learning models using popular frameworks (e.g., TensorFlow, PyTorch ...

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Multimodal Learning information

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are the key skills and qualifications needed to thrive as a Multimodal Learning Specialist, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

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

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.
What are popular job titles related to Multimodal Learning jobs in Minnesota? For Multimodal Learning jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Multimodal Learning jobs in Minnesota look for? The top searched job categories for Multimodal Learning jobs in Minnesota are:
What cities in Minnesota are hiring for Multimodal Learning jobs? Cities in Minnesota with the most Multimodal Learning job openings:
Multimodal Learning jobs near you
Data Scientist - Research Sovereign AI

Data Scientist - Research Sovereign AI

Mayo Clinic

Rochester, MN • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 14 days ago

Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

130th of 871 rated healthcare providers

Job description

Job Description
Data Scientist Foundational Model Science
Position Summary
The Data Scientist for Foundational Model Science is the senior technical leader, and the lead scientist responsible for designing, training, and governing Mayo's multimodal foundational model. This model forms the core intelligence layer used by clinical departments, researchers, agentic workflows, and sovereign AI collaborations. The individual will work as a hands-on architect, model-builder, and researcher while acting as a player-coach, guiding strategy and building a future team.
Key Responsibilities
Scientific & Technical Leadership
  • Design multimodal foundational model architectures integrating signals from imaging, text, waveforms, structured data, graph representations, and temporal embeddings.
  • Develop fusion, alignment, and cross-modal reasoning mechanisms (early fusion, late fusion, token-level fusion, hybrid models).
  • Define and implement methods for grounded clinical reasoning, retrieval-augmented inference, graph-augmented attention, and chain-of-thought verification.
  • Establish protocols for model lifecycle governance, safe update cycles, drift-aware re-training, and provenance tracking.

Hands-On Modeling & Training
  • Train large-scale deep learning models, including multimodal architectures and domain-specific transformer-based systems, on real clinical datasets.
  • Fine-tune and adapt large language models (LLMs) for clinical reasoning, summarization, question answering, agentic behavior, and instruction-following tasks.
  • Build retrieval-augmented pipelines using embeddings, vector stores, graph traversal, and clinically grounded context construction.
  • Develop evaluation methods for reasoning quality, temporal prediction accuracy, multimodal synergy, ablation-based robustness, and counterfactual behavior.
  • Create reference-grounded training datasets, structured reasoning tasks, and multimodal benchmarks to evaluate model performance.
  • Conduct hands-on experimentation with optimization strategies, large-scale distributed training, model quantization, and inference acceleration.
  • Implement uncertainty modeling, selective prediction, abstention mechanisms, and clinically meaningful risk thresholds.
  • Build interpretable reasoning pathways, cross-modal attribution maps, and reference-grounded explanations.

Cross-functional Collaboration
  • Work closely with the Representation team to ensure representation-model alignment.
  • Partner with clinical SMEs to encode domain reasoning into reinforcement learning, preference optimization, or rule-guided behaviors.

Team Leadership
  • Serve as the future founding technical lead of the Foundational Model Science Program.
  • Mentor scientists and engineers and eventually build a specialty modeling team.

Qualifications
Required
  • PhD in Machine Learning, Computer Science, Applied Mathematics, or related discipline with at least four years of informatics, Artificial Intelligence, data science and/or machine learning.
  • Experience with generative modeling, reasoning models, or multimodal foundation models.
  • Expertise in alignment methods (contrastive learning, RLHF/RLCS, preference optimization).
  • Experience with distributed training, and large-scale compute.

Preferred
  • Experience with clinical or EMR data across multiple modalities.
  • 7+ years experience training deep learning models, including transformers or multimodal architectures.
  • Experience defining evaluation frameworks for reasoning, multimodal synergy, reliability, or fairness.
  • Publications in multimodal learning, foundation models, or reasoning architectures.

About Us
Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.
Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.

About the Team
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.
Equal Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

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About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919

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