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Deep Learning Jobs in Massachusetts (NOW HIRING)

Your role will be to use and develop cutting edge deep learning models to guide materials discovery and display design. This work will take place in a rapidly growing team developing new processes to ...

Your role will be to use and develop cutting edge deep learning models to guide materials discovery and display design. This work will take place in a rapidly growing team developing new processes to ...

Research, design, and implement efficient deep learning models forindustrialmachine vision tasks,with a focus on algorithms with low power, low latency and data efficiency requirements * Collaborate ...

Research, design, and implement efficient deep learning models for industrial machine vision tasks, with a focus on algorithms with low power, low latency and data efficiency requirements

Build the next-generation information extraction product powered by state-of-the-art AI and Deep Learning techniques. * Work with an international top-notch engineering team with full commitment on ...

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$12K

$91.6K

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How much do deep learning jobs pay per year?

As of Jun 10, 2026, the average yearly pay for deep learning in Massachusetts is $91,613.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,600.00 and $151,800.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a Deep Learning professional?

As a Deep Learning professional, your day-to-day tasks often include designing and training neural network models, preprocessing and analyzing large datasets, and evaluating model performance using various metrics. You may also participate in research activities, document your results, and collaborate with data scientists, engineers, or product teams to deploy machine learning solutions. Regular meetings for project updates, code reviews, and brainstorming sessions are common, as is staying updated on advances in the field. This dynamic environment offers both individual and team-based work, providing continuous learning and the opportunity to solve complex, real-world problems.

What are deep learning jobs?

Deep learning jobs involve developing and applying neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. These roles typically require skills in programming languages like Python, experience with frameworks like TensorFlow or PyTorch, and a strong understanding of machine learning concepts. They are common in industries such as technology, healthcare, and finance, often requiring a background in computer science or related fields.

What is a Deep Learning job?

A Deep Learning job involves designing, developing, and optimizing neural networks to solve complex problems such as image recognition, natural language processing, and autonomous systems. Professionals in this field work with large datasets, neural network architectures, and frameworks like TensorFlow or PyTorch. They collaborate with data scientists, engineers, and researchers to improve model accuracy and efficiency. Deep Learning roles typically require strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration.

What are the key skills and qualifications needed to thrive in the Deep Learning position, and why are they important?

To thrive in Deep Learning, you need a solid understanding of machine learning theory, neural networks, mathematics (especially linear algebra and probability), and programming skills, typically backed by a degree in computer science, mathematics, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with data preprocessing, and optionally industry-recognized certifications are advantageous. Strong analytical thinking, problem-solving skills, and the ability to communicate findings clearly are crucial soft skills. These abilities enable the design, implementation, and optimization of effective deep learning solutions in real-world applications.

What are the most commonly searched types of Deep Learning jobs in Massachusetts? The most popular types of Deep Learning jobs in Massachusetts are:
Research Fellow - Deep Learning

Research Fellow - Deep Learning

Mass General Brigham

Boston, MA • On-site

Full-time

Posted 26 days ago


Brigham and Women's Hospital rating

8.0

Company rating: 8.0 out of 10

Based on 98 frontline employees who took The Breakroom Quiz

125th of 997 rated hospitals


Job description

Site: Massachusetts Eye and Ear Infirmary
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Qualifications
Postdoctoral Fellow in Deep Learning
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Responsibilities include but may not be limited to
  • Experimental data collection and processing
  • Development and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disorders
  • Clinical translation and implementation of the developed algorithms and interactions with clinicians for their testing
  • Establishment of new and fostering of existing collaborations
  • Participation in the regulatory aspects of clinical translation and patenting
  • Presentation of the results at the scientific meetings and publication of journal articles
  • Mentoring junior staff

Qualifications and Skills
  • PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fields
  • Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
  • Experience with neuroimaging data processing
  • Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
  • Knowledge and experience with cloud-based computational platforms (e.g., AWS)
  • Excellent verbal and written communication skills
  • Strong publication record and academic credentials
  • Ability to work effectively both independently and in collaboration with multiple investigators

Additional Job Details (if applicable)
Remote Type
Onsite
Work Location
243-245 Charles Street
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
EEO Statement:
5110 Massachusetts Eye and Ear Infirmary is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership "looks like" by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

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