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Multimodal Learning Jobs in Boston, MA (NOW HIRING)

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Experience with foundation models, generative AI, self-supervised learning, multimodal learning, or other advanced AI approaches applied to medical imaging. * Expertise in model deployment and ...

Abbott

Staff AI/ML Engineer

Westford, MA

$99K - $198K/yr

Experience with foundation models, generative AI, self-supervised learning, multimodal learning, or other advanced AI approaches applied to medical imaging. * Expertise in model deployment and ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Experience with foundation models, generative AI, self-supervised learning, multimodal learning, or other advanced AI approaches applied to medical imaging. * Expertise in model deployment and ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... Design and implement efficient and scalable MLLM models for inference and analysis of multimodal ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Design and implement efficient and scalable MLLM models for inference and analysis of multimodal ... Learning & Development programs * And yes, we have snacks in our offices Benefits listed herein may ...

VideaHealth

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in ... Depending on your background, that might mean predictive and tabular modeling, multimodal systems ...

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All JobsMultimodal Learning JobsMultimodal Learning Jobs in Boston, MA

Multimodal Learning information

See Boston, MA salary details

$22.8K

$67K

$124.4K

How much do multimodal learning jobs pay per year?

As of Jul 20, 2026, the average yearly pay for multimodal learning in Boston, MA is $67,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,500.00 and $78,200.00 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?

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 Boston, MA? For Multimodal Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Multimodal Learning jobs in Boston, MA look for? The top searched job categories for Multimodal Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Multimodal Learning jobs? Cities near Boston, MA with the most Multimodal Learning job openings:
Multimodal Learning jobs near you
Infographic showing various Multimodal Learning job openings in Boston, MA as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $67,022 per year, or $32.2 per hour.
Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI - AI/CS-Oriented Role

Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI - AI/CS-Oriented Role

Boston College

Chestnut Hill, MA

$53K - $72K/yr

Other

Re-posted 15 days ago

Boston College rating

8.7

Company rating: 8.7 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

47th of 555 rated colleges and universities

Job description

Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI

Boston College, Department of Computer Science
Salary Range: 66,000-75,813 (commensurate with experience)
The labs of Dr. Yuan Yuan and Dr. Donglai Wei in the Department of Computer Science at Boston College invite applications for Postdoctoral Research Fellows to join a highly interdisciplinary team at the intersection of artificial intelligence, health, and neuroscience.

This position focuses on developing next-generation multimodal foundation models and agentic AI systems that can reason across visual, textual, and biomedical data modalities. While one major application area is biomedical and neuroscience imaging, the research will emphasize core AI challenges in representation learning, generative modeling, and agentic intelligence. The successful candidate will have the opportunity to contribute to both fundamental AI research and high-impact scientific applications.
Key Responsibilities

  • Develop and implement novel AI models and learning algorithms for multimodal and generative modeling.
  • Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving multimodal biomedical and neuroscience data.
  • Publish high-quality research in top AI/ML conferences and high-impact scientific journals.
  • Mentor graduate and undergraduate students, and contribute to a collaborative research environment.
  • Participate in proposal development, grant writing, and research management.
  • This is a full-time, one-year appointment with a competitive salary and benefits package, renewable for additional years based on performance and funding availability. The start date is flexible, depending on the candidate's availability.

Applicants should submit:

  • A cover letter describing research interests and fit for the position.
  • A curriculum vitae (CV).
  • Names and contact information of two references (references will only be contacted for shortlisted candidates).
  • For inquiries, please contact Prof. Yuan Yuan (yuanyua@bc.edu) and Prof. Donglai Wei (donglai.wei@bc.edu).

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