ZipRecruiter

Log In

2

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

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 ...

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 ...

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 ...

previous page

Showing results 41-60

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

Remote Machine Learning information

See Lynn, MA salary details

$26.3K

$43.9K

$90.8K

How much do remote machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote machine learning in Lynn, MA is $43,921.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 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.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What cities near Lynn, MA are hiring for Remote Machine Learning jobs? Cities near Lynn, MA with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Lynn, MA as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $43,921 per year, or $21.1 per hour.

Director, Prediction and ML Planning

Motional

Boston, MA • On-site, Remote

Other

Re-posted 10 days ago

Job description

About Motional:

Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation.
Mission Summary:

Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.

As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion.
Core Responsibilities:

  • Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.
  • Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. 
  • Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.
  • Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards.
Required Qualifications & Experience:
  • Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.
  • Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably-balancing technical debt, architectural scalability, and team well-being.
  • ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.
  • Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.
  • Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs).
  • Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning.
Preferred Qualifications:
  • Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.
  • A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.
  • Experience building large-scale data pipelines and training infrastructure required to train large driving models.

 We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote.

Apply