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Multimodal Learning Jobs in Austin, TX (NOW HIRING)

webAI

Director of Applied AI

Austin, TX · On-site

... and multimodal models for domain-specific applications. • Oversee technical execution across ... Every leader in this company is hands-on. • 8+ years of experience in applied machine learning ...

Minnstate

Adjunct Chemistry Teacher

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct Music Instructor

Austin, TX · On-site

$24K - $52K/mo

... distance learning strategies like D2L. * Willingness to teach multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct History Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct English Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct Psychology Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct Speech Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct Math Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Minnstate

Adjunct Biology Instructor

Austin, TX · On-site

... learning strategies like D2L. * Willingness to teach in-person and multimodal courses. * Bilingual/multilingual fluent in Spanish, Karen, Karenni, Somali, Pohnpeian, French, Nuer, Anuak, or other ...

Cisco

Applied AI Scientist

Austin, TX · On-site

... multimodal machinegenerated data - including logs, time series, traces, and events! We combine deep ... Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE ...

webAI Inc

Director of Applied AI

Austin, TX · On-site

... and multimodal models for domain-specific applications. * Oversee technical execution across ... Strong expertise with LLMs, generative AI, machine learning workflows. * Hands-on experience ...

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Showing results 21-40

All JobsMultimodal Learning JobsMultimodal Learning Jobs in Austin, TX

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 are popular job titles related to Multimodal Learning jobs in Austin, TX?

For Multimodal Learning jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Multimodal Learning jobs in Austin, TX look for?

The top searched job categories for Multimodal Learning jobs in Austin, TX are:

What cities near Austin, TX are hiring for Multimodal Learning jobs?

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

Multimodal Learning jobs near you

Director of Applied AI

webAI

Austin, TX • On-site

Full-time

Re-posted 4 days ago

Job description

Job Summary:
webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. The Director of Applied AI will lead a cross-functional team to design, develop, and deploy advanced AI solutions for public sector and enterprise customers, ensuring alignment with customer missions and business goals.
Responsibilities:
• Lead the design, development, and deployment of applied AI systems built on webAI’s distributed AI platform.
• Engage directly with public sector and commercial customers to translate mission needs into technical requirements and scalable solutions.
• Guide teams in training, fine-tuning, optimizing, and evaluating large language models and multimodal models for domain-specific applications.
• Oversee technical execution across multiple parallel projects, ensuring high-quality delivery under tight deadlines.
• Collaborate with Infrastructure, Platform Engineering, and Product teams to align applied AI initiatives with overall product strategy.
• Build and mentor a high-performing applied AI team, fostering a culture of innovation, ownership, and hands-on problem solving.
• Drive architectural decisions related to edge inference, distributed processing, privacy-preserving AI, and real-time performance.
• Establish rigorous evaluation methodologies, benchmarks, and validation frameworks for AI model performance and system reliability.
• Identify emerging trends, technologies, and research areas that can accelerate mission impact and product differentiation.
• Present complex technical concepts to leaders, customers, and stakeholders in a clear and compelling manner.
Qualifications:
Required:
• You need to code! Every leader in this company is hands-on.
• 8+ years of experience in applied machine learning, AI engineering, or related fields, with at least 3 years in a leadership role.
• Proven track record designing and deploying an AI product.
• Strong expertise with LLMs, generative AI, machine learning workflows.
• Hands-on experience building or integrating AI systems for customer-facing applications.
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX, etc.).
• Experience leading cross-functional teams and managing multiple high-impact projects simultaneously.
• Ability to communicate complex technical ideas clearly to both technical and non-technical audiences.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field.
Preferred:
• Master's or PhD in a technical discipline such as Computer Science, Machine Learning, AI, or Applied Mathematics.
• Background in distributed systems, edge computing, or privacy-preserving ML.
• Experience deploying AI models on-device or in constrained compute environments.
• Familiarity with MLOps, data pipelines, and scalable inference architectures.
• Strong understanding of security, compliance, and data governance considerations in enterprise or public sector contexts.
• Ability to thrive in ambiguous, fast-paced, high-growth startup environments.
Company:
The leader in private AI. Founded in 2020, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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