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Multimodal Learning Jobs in Utah (NOW HIRING)

Kforce Technology Staffing

AI Engineer

Draper, UT

Design, build, and optimize machine learning models, including classification, regression ... Practical experience with LLMs, including prompt engineering, API/SDK integration, multimodal ...

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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 Utah? For Multimodal Learning jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Multimodal Learning jobs in Utah look for? The top searched job categories for Multimodal Learning jobs in Utah are:
What cities in Utah are hiring for Multimodal Learning jobs? Cities in Utah with the most Multimodal Learning job openings:
Multimodal Learning jobs near you

Senior Machine Learning Engineer

University of Utah Health

Salt Lake City, UT • On-site

$101K - $138K/yr

Full-time

Medical, Dental

Posted 17 days ago

University Of Utah Health rating

7.6

Company rating: 7.6 out of 10

Based on 139 frontline employees who took The Breakroom Quiz

187th of 874 rated healthcare providers

Job description

Overview
As a patient-focused organization, University of Utah Health exists to enhance the health and well-being of people through patient care, research and education. Success in this mission requires a culture of collaboration, excellence, leadership, and respect. University of Utah Health seeks staff that are committed to the values of compassion, collaboration, innovation, responsibility, integrity, quality and trust that are integral to our mission. EO/AA
Senior Machine Learning Engineers leverage their engineering expertise to solve a variety of technical problems for some of the most challenging and impactful projects in healthcare informatics and machine learning. You will work on a specific project critical to our needs with the opportunity to switch teams and projects as you and our fast-paced business grow. We need machine learning engineers who are versatile, rigorous, display leadership qualities and are enthusiastic to take on new problems. You will design, develop, test, deploy, maintain and enhance machine learning and AI solutions.You will be part of the Innovation Office, a product factory inside the health system of the University of Utah.
Corporate Overview: University of Utah Health is an integrated academic healthcare system with five hospitals including a level 1 trauma center, eleven community health centers, over 1,600 providers, and a health plan serving over 200,000 members. University of Utah Health is nationally ranked and recognized for our academic research, quality standards and overall patient experience. In addition to our clinical delivery system, we have a School of Medicine, School of Dentistry, College of Nursing, College of Pharmacy, and College of Health providing education and training for over 1,250 providers annually. We have over 2 million patient visits annually and research grants exceeding $350 million. University of Utah Hospitals and Clinics represents our clinical operations for the larger health system.
Responsibilities
Essential Functions
  • Creating, managing, maintaining, and refactoring ML codebases, pipelines, and workflows for the innovation office.
  • Collaborating closely with research, medical, and engineering staff to design and implement ML approaches.
  • Implementing scalable ML methods and workflows for high-performance computing (HPC) resources, in close collaboration with research staff and technical staff.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Troubleshooting data analysis issues, including implementation issues, hyper-parameter choices and modeling decision.
  • Assisting in preparation of manuscripts and dissemination of results in the appropriate venues.
  • Conducing tasks independently and communicate optimally to team members and stakeholders.
  • Developing deployable solutions for the health care system.
Knowledge / Skills / Abilities
  • Hands-on coding in C++, Python, PyTorch, or Tensorflow.
  • Foundational understanding of supervised and unsupervised learning, reinforcement learning, and machine learning.
  • Independently execute in the face of ambiguity
  • Leads identifications of dependencies and the development of design documents for a product, application, service, or platform.
  • Write efficient systems code and tests and able to debug distributed systems.
  • Work on-call to monitor systems/product/service for degradation, downtime or interruptions.
  • Innovative mindset with a keen eye for identifying opportunities for improvement.
  • Ability to thrive in a fast-paced, dynamic environment and simultaneously handle multiple projects.
  • Partner effectively with other engineers, product managers, and stakeholders.

Qualifications
Required
  • Bachelor's degree in a relevant field.
  • 5 years of experience in software engineering.

Qualifications (Preferred)
Preferred
  • Experience working in complex academic medical center environments.
  • Experience with large multimodal health datasets.
  • Experience with lifecycle management in a fast-paced software environment.
  • Experience in shipping products and scalable, reliable services.
  • Hands on experience with asynchronous programming and concurrency (threads, tasks, futures, async/await).
  • Experience with Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS), and/or Google Kubernetes Engine (GKE) '
  • Experience in building database engines, query engines, indexing solutions (columnar, full-text, vector), at scale.
  • Experience with programming CUDA, AI systems at scale.
  • Experience with live site operations, Site Reliability Engineering (SRE) or production support roles.
  • Experience in networking, distributed systems, lower-level infrastructure.
  • Experience developing accessible technologies.
  • Proficiency in code and system health, diagnosis and resolution, and software test engineering.
  • Experience with AI agents.
Working Conditions and Physical Demands
Employee must be able to meet the following requirements with or without an accommodation.
  • This is a sedentary position that may exert up to 10 pounds and may lift, carry, push, pull or otherwise move objects. This position involves sitting most of the time and is not exposed to adverse environmental conditions.

Physical Requirements
Listening, Sitting, Speaking, Standing, Walking

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