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Multimodal Learning Jobs in Austin, TX (NOW HIRING)

... active, multimodal, and sustainable transportation. If you are looking to join an innovative ... learning. Required This position requires a combination of skills, experience and education ...

Material Handler 2

Austin, TX · On-site

$16.50 - $20/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

Material Handler 2

Austin, TX

$16.50 - $20/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

TDM Program Manager

Austin, TX · On-site

$80K - $110K/yr

... active, multimodal, and sustainable transportation. If you are looking to join an innovative ... engaging in continuous learning and integrating this knowledge into projects, including an ...

... generation, multimodal inference, and long‑context workloads. * Instrument and analyze ... Experience applying machine learning techniques to systems optimization or performance analysis.

Senior Engineering Manager, AI

Austin, TX · On-site

$234K - $296K/yr

... multimodal machinegenerated data - including logs, time series, traces, and events. We combine deep ... learning systems, large language models, andproductionAI platforms as you will: * Lead and develop ...

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Multimodal Learning information

See Austin, TX salary details

$20.8K

$61.1K

$113.5K

How much do multimodal learning jobs pay per year?

As of Aug 18, 2026, the average yearly pay for multimodal learning in Austin, TX is $61,150.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,600.00 and $71,400.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive in multimodal learning, 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 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 cities near Austin, TX are hiring for Multimodal Learning jobs?

Cities near Austin, TX with the most Multimodal Learning job openings:

Endowed Chair in Digital Humanities

Texas State University

San Marcos, TX • On-site

Full-time

Re-posted 10 days ago


Texas State University rating

6.3

Company rating: 6.3 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

533rd of 618 rated colleges and universities


Job description

Posting Information
Posting Information
Position Title
Endowed Chair in Digital Humanities
Job Posting Number
2026081TTL
Job Location
San Marcos
Department
Office of the Provost and EVPAA
Position Description
Texas State University seeks applications for an endowed chair at the rank of Professor to conduct research on any aspect of Digital Humanities. Texas State University seeks to establish a leadership position in Digital Humanities scholarship to complement existing strengths in interdisciplinary research that bridges humanistic inquiry with innovative digital methods, computational analysis, archival technologies, data visualization, public-facing humanities work, and critical digital studies. Texas State is home to multiple humanities-focused research initiatives that support data-intensive and computational approaches to humanistic questions.
Texas State University receives a full share of the Texas University Fund (TUF) and plans to invest funds in recruitment and substantial start-up support for strategic hires with established research programs and active external funding in historic and emerging areas of research strength, including Digital Humanities.
We seek to hire dynamic and innovative scholars with an exceptionally strong research record supported by external funding. An applicant's scholarly focus should complement and enhance the Digital Humanities scholarship and teaching strengths of Texas State, such as:
  • Digital Humanities across the Disciplines
  • Digital Cultural Heritage, Preservation & Archives
  • Text Mining, Corpus Analysis & Natural Language Processing for Humanities
  • Spatial Humanities & GIS
  • Computer-assisted Language Instruction and Translation
  • Humanities-Based Approaches to Technology Policy
  • Critical Digital Studies & Digital/AI Ethics
  • Humanities-Based Approaches to Technology Policy
  • Digital Storytelling, Multimedia Production & Media Archaeology
  • Multimodal / Digital Rhetoric and Communication Studies
  • Digital Pedagogy & Learning Environments
  • Humanities-Based Approaches to Technology Policy
  • Community-Engaged Digital Humanities

Responsibilities:
  • Seek external funding and coordinate interdisciplinary grants with both internal and external collaborators.
  • Conduct and publish original research on Digital Humanities.
  • Lead interdisciplinary collaboration with faculty across the university.
  • Develop and maintain an active research agenda.
  • Teach undergraduate and graduate courses on Digital Humanities and related subjects.
  • Mentor and advise students.
  • Contribute to the development of the Digital Humanities curriculum.
  • Participate in service activities at the department, college, and university levels.

The successful candidate will join the department(s) appropriate to their area of scholarly focus. The successful candidate will be nationally recognized in their field.
Required Qualifications
  • Ph.D. or terminal degree.
  • Evidence of a scholarly focus and sustained record of research excellence in Digital Humanities
  • Evidence of sustained record of excellence in teaching and mentoring students.
  • Evidence of a sustained record of obtaining external funding.

Preferred Qualifications
  • Evidence of experience supporting or running humanities infrastructure such as centers or groups.
  • Evidence of activity in organizing conferences and sessions in Digital Humanities.
  • Experience in teaching and mentoring both undergraduate and graduate students.
  • Experience supporting experiential learning for undergraduate and graduate students.
  • Strong commitment to interdisciplinary collaboration.
  • Evidence of community engagement for scholarship and teaching.

Application Procedures
Applications will be considered on a rolling basis. Only applications submitted through the Texas State University website will be accepted and considered: https://jobs.hr.txstate.edu/postings/56610Interested applicants should submit the following materials:
  • A cover letter highlighting scholarly focus, publications, teaching, and external funding.
  • A detailed curriculum vitae.
  • Unofficial transcripts (all in one document).
  • The names and contact information of three references.

The selected candidate will be required to provide official transcripts from all degree granting universities.
Proposed Start Date
Fall 2026 (negotiable)
Posting Date
04/10/2026
Review Date
10/30/2026
Close Date
Open Until Filled?
Legal Notices
Texas State University is committed to a policy of non-discrimination and equal opportunity for all persons regardless of race, sex, color, religion, national origin or ancestry, age, marital status, disability, veteran status, or any other basis protected by federal or state law in employment, educational programs, and activities and admissions.
Employment with Texas State University is contingent upon the outcome of record checks and verifications including, but not limited to, criminal history, driving records, education records, employment verifications, reference checks, and employment eligibility verifications.
This position may conduct research on critical infrastructure depending on the research focus of a hire. Consistent with the requirements of the State of Texas, individuals conducting research on critical infrastructure will be subject to pre-employment, and then subsequent routine background checks/cybersecurity screenings. Employment will at all times be contingent upon the successful completion of these screenings in accordance with State and University requirements.
Reasonable Accommodation
If you experience accessibility issues or require alternative formatting during the application process due to a disability or underlying condition, we request that you contact Talent Acquisition for assistance. A representative from Talent Acquisition will respond to you as soon as possible.
Record Checks and Verifications
Employment with Texas State University is contingent upon the outcome of record checks and verifications including, but not limited to, criminal history, driving records, education records, employment verifications, reference checks, and employment eligibility verifications.
Eligibility for Employment
In accordance with federal law, all new employees must complete the Form I-9 and provide acceptable documentation verifying their identity and authorization to work in the United States. Texas State University participates in E-Verify, and employment is contingent upon the successful verification of work authorization. Employees are required to maintain valid work authorization to satisfy the conditions of Form I9 at all times during their employment and the university makes no implicit or explicit promises to financially support visa or permanent residency applications.
Why Work at Texas State?
Texas State University is a large, student-centered public research institution serving more than 40,000 students across undergraduate, graduate, and doctoral programs in San Marcos and Round Rock. Classified as a Carnegie Doctoral University with High Research Activity (R2), TXST is actively advancing its ambitious Run to R1 strategy, demonstrating sustained growth in research activity, doctoral education, and scholarly impact.
Faculty at TXST join a vibrant academic community of over 5,000 faculty and staff committed to excellence in teaching, research, and service. The university offers a collaborative, supportive environment, and interdisciplinary scholarship. Outstanding faculty are drawn to TXST for the opportunity to make a meaningful impact-advancing research, mentoring a growing student body, and helping shape the future of a rapidly growing research university.
Quick Link
https://jobs.hr.txstate.edu/postings/56610

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