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Remote Medical Imaging Machine Learning Jobs in Cumberland, RI

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in ... LI-Remote We value diversity and believe the unique contributions each of us brings drives our ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global ... Our comprehensive employee benefits include bonuses, medical, dental, vision, life insurance, AD&D ...

Join Our Team At 626, we're more than a medical imaging service company - we're a team of problem ... machines. * Accurately document all service activities in accordance with the Company Quality ...

Discovery Imaging Sales Specialist

Boston, MA · On-site +1

$105K - $120K/yr

... and Medical company located in the Boston and Cambridge metro area and will be fully remote. At ... Imaging Sales Specialists provide camera imager (Amersham IQ800), laser scanner (Amersham Typhoon ...

Showing results 21-40

Remote Medical Imaging Machine Learning information

What is a remote medical imaging machine learning specialist?

A remote medical imaging machine learning specialist is a professional who develops and applies machine learning algorithms to analyze medical images, such as X-rays, MRIs, and CT scans, from a remote location. They work with healthcare providers and researchers to improve diagnostic accuracy and streamline image analysis, often using artificial intelligence techniques. This role typically requires expertise in both medical imaging technologies and advanced machine learning, as well as the ability to collaborate virtually with multidisciplinary teams. Their work helps enable faster, more precise medical diagnoses and can contribute to advances in telemedicine.

How does a remote medical imaging machine learning professional typically collaborate with radiologists and other healthcare experts?

Remote Medical Imaging Machine Learning professionals work closely with radiologists, data scientists, and IT teams to develop and refine AI models for diagnostic imaging. Collaboration often occurs through virtual meetings, shared data annotation platforms, and cloud-based model deployments. Regular feedback from radiologists is essential to ensure the models provide clinically relevant and accurate outputs. This teamwork helps bridge the gap between technical development and real-world clinical needs, leading to more effective and reliable imaging solutions.

What are the key skills and qualifications needed to thrive as a remote medical imaging machine learning specialist, and why are they important?

To excel as a Remote Medical Imaging Machine Learning Specialist, you need a solid background in computer science, mathematics, and medical imaging, often supported by a relevant degree (such as in computer science, biomedical engineering, or a related field) and experience with machine learning frameworks. Familiarity with technical tools like Python, TensorFlow, PyTorch, and DICOM imaging systems, along with experience in medical imaging data annotation and model deployment, is typically required. Strong analytical thinking, attention to detail, and effective remote communication skills help differentiate top performers in this field. These competencies ensure the accurate development and deployment of AI models that support clinical decision-making and improve patient outcomes in healthcare environments.

What cities near Cumberland, RI are hiring for Remote Medical Imaging Machine Learning jobs?

Cities near Cumberland, RI with the most Remote Medical Imaging Machine Learning job openings:

Algorithm Engineer

Beacon Biosignals

Boston, MA • On-site, Remote

$150K - $170K/yr

Full-time

PTO

Re-posted 6 days ago


Key responsibilities

  • Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation.

  • Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.

  • Enhance internal deep learning and machine learning tools to improve team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase for reusability to enable rapid experimentation.


Job description

Beacon Biosignals is seeking a Machine Learning engineer! 

As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data scientists, neuroscientists, engineers, and clinicians to scope, build, deploy, and maintain the machine and deep learning models that analyze brain and biosignal data for advancing sleep, neurological, and psychiatric therapy development.

At Beacon, we've found that cultural and scientific impact is driven most by those who lead by example. As such, we're always seeking out new contributors whose work demonstrates innate curiosity, a bias toward simplicity, an eye for composability, a self-service mindset, and-most of all-a deep empathy toward colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.

Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston, New York City and Paris.

What success looks like

  • Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation.
  • Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.
  • Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation.
  • Spread and improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing.
  • Present results to key stakeholders and assist them in utilizing algorithms for client engagement.
  • Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development.

What you will bring

  • You have more than 4 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production.
  • You are experienced with digital signal processing (DSP) and statistics and care about using the right tool for the job, which in many cases might not be machine learning or deep learning.
  • You are proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
  • You are familiar with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
  • You follow and adopt best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
  • You are familiar with biosignals, medical imaging data, or large time-series datasets,  or are enthusiastic about learning more in the domain.
  • You thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.
  • You are able to distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally.
  • You are excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms.

The US-based salary range for this role is $150,000 - $170,000. Salary ranges are determined using current market compensation data for this role and adjusted based on experience, skills, and location. The base salary is one component of the total compensation package, which includes equity, PTO and other benefits.

At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.

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