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

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

Beacon Biosignals is seeking a Machine Learning engineer! At Beacon, we've found that cultural and ... Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we ...

Beacon Biosignals

Senior Algorithm Engineer

Boston, MA · On-site +1

$113K - $155K/yr

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

Motional

Director, Prediction and ML Planning

Boston, MA · On-site +1

$288K - $396K/yr

Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

The Phia Group

Data Engineer (Remote)

Canton, MA · On-site +1

$121K - $145K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ML workflows (e.g., batch/real-time scoring) * Continually improve ongoing reporting and analytics ...

The Phia Group

Data Engineer (Remote)

Canton, MA · On-site +1

$121K - $145K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ML workflows (e.g., batch/real-time scoring) * Continually improve ongoing reporting and analytics ...

3Play Media

Senior Applied Data Scientist

Boston, MA · On-site +1

$150K - $180K/yr

... machine learning, natural language processing, generative AI, signal processing, applied ... Remote -- United States Employment type: Full-time About 3Play Media 3Play Media is a technology ...

Adidev Technologies Inc

ML/AI Engineers

Boston, MA · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

OneStudyTeam

Senior Data Scientist

Boston, MA · On-site +1

$140K - $190K/yr

In this position, you will drive the development of statistical models and machine learning ... LI-Remote We value diversity and believe the unique contributions each of us brings drives our ...

Redhat

Software Engineer

Boston, MA · On-site +1

$178K - $195K/yr

Create open-source software in the machine learning and data science pipelines domain ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Somerville, MA

Remote Machine Learning information

See Somerville, MA salary details

$27.8K

$46.5K

$96K

How much do remote machine learning jobs pay per year?

As of Jul 21, 2026, the average yearly pay for remote machine learning in Somerville, MA is $46,471.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $50,200.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Somerville, MA? The most popular types of Machine Learning jobs in Somerville, MA are:
What are popular job titles related to Remote Machine Learning jobs in Somerville, MA? For Remote Machine Learning jobs in Somerville, MA, the most frequently searched job titles are:
What cities near Somerville, MA are hiring for Remote Machine Learning jobs? Cities near Somerville, MA with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Somerville, MA as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $46,471 per year, or $22.3 per hour.
Algorithm Engineer

Algorithm Engineer

Beacon Biosignals

Boston, MA • On-site, Remote

Full-time

PTO

Re-posted 17 days ago

Job description

Beacon Biosignals is on a mission to revolutionize precision medicine for the brain. We are the leading at-home EEG platform supporting clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker discovery and implementation. Beacon's Clinico-EEG database contains EEG data from nearly 100,000 patients, and our cloud-native analytics platform powers large-scale RWD/RWE retrospective and predictive studies. Beacon Biosignals is changing the way that patients are treated for any disorder that affects brain physiology.
Beacon Biosignals is seeking a Machine Learning engineer!
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 base salary range for this role is determined based on past experience, specific skills and qualifications. 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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