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Multimodal Learning Jobs in Leander, TX (NOW HIRING)

Responsibilities : • Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures • Conduct research on model efficiency ...

You'll architect and implement Vision-Language-Action (VLA) models, advance reinforcement learning applications, and push the boundaries of multimodal AI integration. This role combines deep ...

Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures * Conduct research on model efficiency, quantization, compression, and ...

Transformers and multimodal models opened up approaches that weren't available two years ago. Part ... Python and a modern deep learning framework , fluently, as your daily working environment. * Enough ...

Machine Learning Engineer

Austin, TX · On-site

$138K/yr

Transformers and multimodal models opened up approaches that weren't available two years ago. Part ... Python and a modern deep learning framework , fluently, as your daily working environment. * Enough ...

Design and implement deep-learning solutions using neural networks, transformers, convolutional architectures, sequence models, representation-learning techniques, and multimodal approaches. * Build ...

The instructor may be assigned to teach in a traditional classroom, a virtual (online) classroom, or both (multimodal). Activities related to comprehensive community college teaching and learning ...

The instructor may be assigned to teach in a traditional classroom, a virtual (online) classroom, or both (multimodal). Activities related to comprehensive community college teaching and learning ...

... multimodal). • Comfortable debugging distributed systems under load. • Bias toward shipping and learning from production behavior. Nice-to-Have Skills: • Experience with Python and NodeJs. • ...

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Multimodal Learning information

See Leander, TX salary details

$20.1K

$58.9K

$109.4K

How much do multimodal learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for multimodal learning in Leander, TX is $58,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,200.00 and $68,800.00 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 Leander, TX?

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

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

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

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

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

Infographic showing various Multimodal Learning job openings in Leander, TX 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, with an average salary of $58,947 per year, or $28.3 per hour.

AI Research Scientist

Austin, TX • On-site

Full-time

Re-posted 26 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 AI Research Scientist will design, train, evaluate, and optimize cutting-edge machine learning models, collaborating with various teams to ensure innovations have real-world impact.
Responsibilities:
• Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures
• Conduct research on model efficiency, quantization, compression, and on-device deployment
• Prototype novel model architectures, training methods, and inference strategies for distributed AI
• Develop and evaluate benchmarks, datasets, and experimental frameworks to test model performance
• Collaborate with engineering teams to integrate research findings into production systems
• Stay current on leading research in deep learning, generative AI, and distributed ML
• Analyze experimental results and communicate insights clearly to technical and non-technical stakeholders
• Document research findings, contribute to internal papers, and present technical work across the organization
• Identify emerging technologies and propose research directions aligned with webAI’s strategic priorities
Qualifications:
Required:
• 4+ years of experience (can be graduate research) in machine learning research, AI model development, or related fields
• Strong expertise in deep learning architectures including transformers, CNNs, RNNs, and diffusion models
• Hands-on experience training and fine-tuning large-scale models
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
• Experience building datasets, designing experiments, and validating ML model performance
• Deep understanding of optimization techniques including quantization, distillation, pruning, and hardware-aware training
• Strong problem-solving skills and ability to work independently on complex research tasks
• Effective communication skills for presenting research findings to diverse audiences
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
Preferred:
• Master’s or PhD in Machine Learning, Computer Science, AI, or a related field
• Experience with distributed training, edge inference, or on-device ML
• Research experience in generative AI, reinforcement learning, or multimodal learning
• Familiarity with privacy-preserving ML techniques such as federated learning
• Experience contributing to academic publications, patents, or open-source ML projects
• Comfort operating in a fast-paced, high-growth startup environment
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.