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Remote Machine Learning Postdoc Jobs in Waltham, MA

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

$150K - $170K/yr

As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data ... Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we ...

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

$150K - $170K/yr

As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data ... Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we ...

FocusKPI Inc.

Data Science Intern

Boston, MA · On-site +1

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... and machine learning models for marketing measurement. This role is designed for someone with ...

FocusKPI Inc.

Data Science Intern

Boston, MA · Remote

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... and machine learning models for marketing measurement. This role is designed for someone with ...

Manulife

Data Engineer

Boston, MA · Remote

$137K/yr

Collaborate with data scientists to build pipelines for training and deploying machine learning ... This position is eligible for fully remote work from any location in the United States. Minimum ...

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

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Remote Machine Learning Postdoc information

What is a remote machine learning postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are the key skills and qualifications needed to thrive as a remote machine learning postdoc?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.

What are popular job titles related to Remote Machine Learning Postdoc jobs in Waltham, MA?

For Remote Machine Learning Postdoc jobs in Waltham, MA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Postdoc jobs in Waltham, MA look for?

The top searched job categories for Remote Machine Learning Postdoc jobs in Waltham, MA are:

What cities near Waltham, MA are hiring for Remote Machine Learning Postdoc jobs?

Cities near Waltham, MA with the most Remote Machine Learning Postdoc job openings:

Remote Machine Learning Postdoc jobs near you
Infographic showing various Remote Machine Learning Postdoc job openings in Waltham, MA as of August 2026, with employment types broken down into 5% Internship, 57% Full Time, 13% Part Time, and 25% Contract. Highlights an 100% Remote job distribution.

Algorithm Engineer

Boston, MA • On-site, Remote

Beacon Biosignals
Software Development • 1 - 10 employees
Learn more about Beacon Biosignalsexternal

$150K - $170K/yr

Full-time

PTO

Re-posted 7 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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