AI Research Scientist
Austin, TX · On-site
Responsibilities : • Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures • Conduct research on model efficiency ...
AI Research Scientist
Austin, TX · On-site
Responsibilities : • Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures • Conduct research on model efficiency ...
You will work at the frontier of vision-language models (VLMs), multimodal learning, robotics AI, and industrial autonomy. You will be developing systems that combine visual perception, language ...
You will work at the frontier of vision-language models (VLMs), multimodal learning, robotics AI, and industrial autonomy. You will be developing systems that combine visual perception, language ...
You will work at the frontier of vision-language models (VLMs), multimodal learning, robotics AI, and industrial autonomy. You will be developing systems that combine visual perception, language ...
You will work at the frontier of vision-language models (VLMs), multimodal learning, robotics AI, and industrial autonomy. You will be developing systems that combine visual perception, language ...
Senior AI / Machine Learning Engineer
Austin, TX · Remote
$115K - $200K/yr
Exposure to multimodal learning or foundation models. * Prior work in startups or fast-moving R&D environments. * Contributions to open-source ML frameworks or research codebases. Note: Prior ...
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Senior AI / Machine Learning Engineer
Austin, TX · Remote
$115K - $200K/yr
Exposure to multimodal learning or foundation models. * Prior work in startups or fast-moving R&D environments. * Contributions to open-source ML frameworks or research codebases. Note: Prior ...
Staff R&D AI Engineer
Austin, TX · On-site
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 ...
Staff R&D AI Engineer
Austin, TX · On-site
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 ...
AI Research Scientist
Austin, TX · On-site
Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures * Conduct research on model efficiency, quantization, compression, and ...
AI Research Scientist
Austin, TX · On-site
Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures * Conduct research on model efficiency, quantization, compression, and ...
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are looking for an experienced Machine Learning Engineer with a strong background ...
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are looking for an experienced Machine Learning Engineer with a strong background ...
Machine Learning Engineer
Austin, TX · On-site
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... Design, implement, and refine deep learning models to ensure efficiency, scalability, and ...
Machine Learning Engineer
Austin, TX · On-site
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... Design, implement, and refine deep learning models to ensure efficiency, scalability, and ...
We're looking for a Machine Learning Engineer to help us design and build the next generation of ... or Large Multimodal Models (LMMs). 5+ years experience with LLMs and transformer-based ...
We're looking for a Machine Learning Engineer to help us design and build the next generation of ... or Large Multimodal Models (LMMs). 5+ years experience with LLMs and transformer-based ...
Senior / Staff Machine Learning Engineer
Austin, TX · On-site
$124K - $171K/yr
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...
Senior / Staff Machine Learning Engineer
Austin, TX · On-site
$124K - $171K/yr
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...
Senior / Staff Machine Learning Engineer
$124K - $171K/yr
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...
Senior / Staff Machine Learning Engineer
$124K - $171K/yr
... and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...
We're looking for a Machine Learning Engineer to help us design and build the next generation of ... or Large Multimodal Models (LMMs). 5+ years experience with LLMs and transformer-based ...
We're looking for a Machine Learning Engineer to help us design and build the next generation of ... or Large Multimodal Models (LMMs). 5+ years experience with LLMs and transformer-based ...
AI Research Director
Austin, TX · On-site
Expertise in modern AI architectures including transformers, diffusion models, multimodal systems, and reinforcement learning * Experience designing, training, and optimizing large-scale ML models
AI Research Director
Austin, TX · On-site
Expertise in modern AI architectures including transformers, diffusion models, multimodal systems, and reinforcement learning * Experience designing, training, and optimizing large-scale ML models
Job#: 3036752 Principal Machine Learning Engineer - Model Efficiency & Optimization Location ... multimodal challenges. * Diagnose and resolve failure modes such as quality degradation and ...
Job#: 3036752 Principal Machine Learning Engineer - Model Efficiency & Optimization Location ... multimodal challenges. * Diagnose and resolve failure modes such as quality degradation and ...
Postdoctoral Fellow - Imaging Genetics
Austin, TX · On-site
$48K - $65K/yr
The lab focuses on: • Integration of imaging-derived traits with genetic data • Multimodal machine learning for biological discovery • Translational genomics and risk modeling The fellow will ...
Postdoctoral Fellow - Imaging Genetics
Austin, TX · On-site
$48K - $65K/yr
The lab focuses on: • Integration of imaging-derived traits with genetic data • Multimodal machine learning for biological discovery • Translational genomics and risk modeling The fellow will ...
... Multimodal architectures. As a Developer Technology Manager, you'll define and lead strategic ... Lead your team to optimize and develop algorithms for Machine Learning and Deep Learning ...
... Multimodal architectures. As a Developer Technology Manager, you'll define and lead strategic ... Lead your team to optimize and develop algorithms for Machine Learning and Deep Learning ...
Nursing AD Instructor
$44K - $101K/yr
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 ...
Nursing AD Instructor
$44K - $101K/yr
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 ...
Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence ...
Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence ...
Lead Robotics Data Engineer
Austin, TX · On-site
$110K - $130K/yr
... multimodal human task data. We are building the operation that solves that. The Lead Robotics Data ... Imitation learning / robot learning pipeline experience * Human teleoperation system operation
Lead Robotics Data Engineer
Austin, TX · On-site
$110K - $130K/yr
... multimodal human task data. We are building the operation that solves that. The Lead Robotics Data ... Imitation learning / robot learning pipeline experience * Human teleoperation system operation
Lead Robotics Data Engineer
$110K - $130K/yr
... multimodal human task data. We are building the operation that solves that. The Lead Robotics Data ... Imitation learning / robot learning pipeline experience * Human teleoperation system operation
Lead Robotics Data Engineer
$110K - $130K/yr
... multimodal human task data. We are building the operation that solves that. The Lead Robotics Data ... Imitation learning / robot learning pipeline experience * Human teleoperation system operation
Multimodal Learning information
See Austin, TX salary details
$20.8K - $29.2K
10% of jobs
$29.2K - $37.7K
14% of jobs
$38.8K is the 25th percentile. Wages below this are outliers.
$37.7K - $46.1K
10% of jobs
$46.1K - $54.5K
12% of jobs
The median wage is $56.5K / yr.
$54.5K - $62.9K
20% of jobs
$68.2K is the 75th percentile. Wages above this are outliers.
$62.9K - $71.4K
15% of jobs
$71.4K - $79.8K
4% of jobs
$79.8K - $88.2K
2% of jobs
$88.2K - $96.6K
4% of jobs
$96.6K - $105.1K
0% of jobs
$105.1K - $113.5K
9% of jobs
$20.8K
$61.1K
$113.5K
How much do multimodal learning jobs pay per year?
As of Jul 27, 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 is the difference between Multimodal Learning vs Data Scientist?
| Aspect | Multimodal Learning | Data Scientist |
|---|---|---|
| Required Credentials | Advanced degrees in AI, Machine Learning, or Computer Science | Bachelor's or Master's in Data Science, Statistics, or related fields |
| Work Environment | Research labs, AI development teams, academia | Business, tech companies, analytics teams |
| Industry Usage | AI research, multimedia applications, robotics | Data 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 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:
Full-time
Posted 7 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 51-200 employees. The company is currently Growth Stage.
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 51-200 employees. The company is currently Growth Stage.