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Multimodal Learning Jobs in Massachusetts (NOW HIRING)

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 ...

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 ...

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 ...

Staff AI/ML Engineer

Westford, MA · On-site

$99.30 - $198.70/hr

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 ...

New

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 ...

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 ...

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 ...

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 ...

Showing results 21-40

Multimodal Learning information

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 in Massachusetts are hiring for Multimodal Learning jobs?

Cities in Massachusetts with the most Multimodal Learning job openings:

Principal Scientist, Machine Learning - Multimodal Biological Reasoning

Flagship Pioneering, Inc.

Cambridge, MA

Full-time

Medical, Retirement

Re-posted 20 days ago


Job description

About Pioneering Intelligence

Pioneering Intelligence builds on Flagship Pioneering's legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship's integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

The Role

Pioneering Intelligence is seeking a Lead for Flagship's ambitious efforts to build polyintelligent AI systems that unify human scientific expertise, machine intelligence, and nature's biological signals into multi-modal, multi-scale reasoning engines for biology.

As Lead, you will have the unique opportunity to shape our biological reasoning efforts on both the technical and application levels. You will be a hands-on lead for a team of talented machine learning scientists innovating on model architectures that will create best-in-class biological reasoning engines. You will be responsible for sourcing high-value use cases across Flagship and its portfolio companies and translating these into requirements to develop the model towards optimal performance on the unconventional life sciences problems that Flagship tackles. You will work with teams in Pioneering Intelligence and Flagship-at-large to apply our reasoning engines to discover new biology and engineer new biological solutions through massively parallel in-silico reasoning. You will have the opportunity to originate and lead multiple projects in this space over time.

Key Responsibilities
  • Own the roadmap: lead the project from architecture and data exploration through model readiness, benchmarking, refinement, and agentic integration.
  • Guide technical architecture through a biological lens: guide multi-modal, multi-scale model design and ensure the system can ingest and reason over modalities relevant to mechanism-of-action reasoning, target discovery, perturbation biology, pathway reasoning, protein function, and autonomous discovery workflows.
  • Translate biology into model and evaluation requirements: ensure model development is driven by biological relevance that enables real scientific workflows, not just benchmark performance or technical elegance.
  • Build the engine for a novel science platform: develop and integrate reasoning engines into Pioneering Intelligence's AI Scientist platform for autonomous science.
  • Source and shape portfolio use cases: interface with Flagship teams and portfolio company end-users to identify use cases, source data assets, define success criteria, and create end-user feedback loops for reasoning engines that are scientifically meaningful, tractable, and answer high-value questions with real world application.
  • Communicate the impact: disseminate strategic direction and scientific results to Flagship stakeholders and in public forums.
Qualifications
  • Industry-leading expertise in modern LLMs, multimodal modeling, representation learning, fine-tuning, post-training, benchmarking, and ML systems.
  • Deep experience in computational biology, AI-for-biology, AI-enabled drug discovery, translational data science, biological foundation models, or scientific discovery platforms.
  • Demonstrated ability to work with scientists or biotech teams to scope high-value use cases, identify data assets, define success criteria, and translate discovery needs into technical execution plans.
  • Working knowledge of biological data modalities such as genomics, transcriptomics, perturbation data, protein sequence, protein structure, pathways, imaging, pathology, or time-series biological data.
  • Strong judgment around mechanism-of-action reasoning, target discovery, perturbation biology, scientific credibility, model limitations, hallucination risk, interpretability, and validation.
  • Experience leading small, high-caliber technical teams through ambiguous scientific or product problems.
  • Ability to communicate clearly with ML researchers, data engineers, portfolio-company scientists, executives, and venture creation leaders.
  • Comfort operating in an entrepreneurial environment where the goal is not only to build a model, but to create a new capability that can reshape company creation and scientific discovery.
Requirements
  • PhD, MS, or equivalent experience in computational biology, machine learning, bioengineering, computer science, systems biology, quantitative biology, translational science, or a related field.
  • Experience in biotech, pharma, AI-for-science, AI drug discovery, venture creation, or a platform organization serving multiple scientific programs.
  • Experience deploying AI/ML for biology systems into scientific workflows at enterprise scale.
  • Experience with LLMs, biological foundation models, protein language models, genomic foundation models, scientific agents, or AI discovery platforms.
  • Experience working across multiple internal and external customers, therapeutic programs, or discovery teams.

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

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The salary range for this role is $216,000 - $297,000. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence's good faith estimate as of the date of publication and may be modified in the future.