2

Remote Machine Learning Jobs in Cambridge, MA (NOW HIRING)

Senior Algorithm Engineer

Boston, MA · On-site +1

$170K - $190K/yr

As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data ... This is a fully remote role based anywhere in the U.S. What success looks like * Participate in and ...

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 ...

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 ...

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 ...

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 ...

Showing results 41-60

Remote Machine Learning information

See Cambridge, MA salary details

$27.9K

$46.5K

$96.2K

How much do remote machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote machine learning in Cambridge, MA is $46,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $50,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Machine Learning jobs in Cambridge, MA?

The most popular types of Machine Learning jobs in Cambridge, MA are:

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

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

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

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

Infographic showing various Remote Machine Learning job openings in Cambridge, MA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, 1% Temporary, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $46,543 per year, or $22.4 per hour.

Senior Algorithm Engineer

Beacon Biosignals

Boston, MA • On-site, Remote

$170K - $190K/yr

Full-time

PTO

Re-posted 23 days ago


Job description

Beacon Biosignals is transforming precision medicine for the brain, from clinical development to clinical care. For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our Diagnostics business is building the most comprehensive at-home platform for precision diagnostics, combining EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders. Together, we're changing the way patients are diagnosed and treated for any disorder that affects brain physiology.
Beacon Biosignals is seeking a Senior Algorithm and 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 work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston, New York City and Paris. This is a fully remote role based anywhere in the U.S.
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 5 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 proficient with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
  • You follow and spread best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
  • You are experienced 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 $170,000 - $190,000. 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.
#LI-Remote