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Remote Machine Learning Architect Jobs in Leominster, MA

micro1 AI

AI Trainer - Microbiology Expert

Worcester, MA · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Lowell, MA · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Brooks Automation, Inc.

Software Engineer

Chelmsford, MA · On-site +1

$105K - $142K/yr

... issues (remote or on-site). WHAT YOU'LL BRING * Proficiency in programming C++11 or later ... Familiarity with Machine Learning. * Familiarity with Python, JavaScript, MATLAB, or similar ...

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All JobsMachine Learning Architect JobsRemote Machine Learning Architect JobsRemote Machine Learning Architect Jobs in Leominster, MA

Remote Machine Learning Architect information

See Leominster, MA salary details

$48.1K

$133.1K

$208.2K

How much do remote machine learning architect jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote machine learning architect in Leominster, MA is $133,059.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $171,500.00 per year, depending on experience, location, and employer.

What is a remote machine learning architect?

A Remote Machine Learning Architect is a professional who designs, builds, and oversees machine learning systems and infrastructure while working remotely. They collaborate with data scientists, engineers, and stakeholders to define system architecture, select appropriate algorithms, and ensure scalable deployment of machine learning models. Their responsibilities include setting technical standards, optimizing workflows, and ensuring integration with existing IT infrastructure, all accomplished through remote communication and collaboration tools. This role requires strong expertise in machine learning, cloud platforms, and software engineering.

How does a remote machine learning architect typically collaborate with distributed teams to deliver successful projects?

As a Remote Machine Learning Architect, effective collaboration with globally distributed teams is essential. You will often coordinate with data scientists, software engineers, and business stakeholders via virtual meetings, shared documentation, and project management tools. Regular communication, clear documentation of model designs, and version control practices are crucial to ensure alignment and smooth integration of machine learning solutions. Adopting agile methodologies and being proactive in addressing time zone differences help maintain project momentum and foster a productive team environment.

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

To thrive as a Remote Machine Learning Architect, you need deep expertise in machine learning algorithms, model development, and a solid background in computer science or related fields, often supported by an advanced degree. Familiarity with cloud platforms (such as AWS, Azure, or GCP), deep learning frameworks (like TensorFlow or PyTorch), and relevant certifications are typically expected. Strong problem-solving, communication, and project management skills help you collaborate effectively with distributed teams and stakeholders. These skills and qualities are crucial for designing scalable ML solutions that drive business value in a remote work environment.

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

AspectRemote Machine Learning ArchitectData Scientist
Required CredentialsMaster's or PhD in CS, AI, or related fields; certifications in ML frameworksMaster's in Data Science, Statistics, or related; certifications in data analysis tools
Work EnvironmentDesigning ML systems, collaborating with engineering teams, remote or on-siteAnalyzing data, building models, often remote or in-office
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Remote Machine Learning Architects focus on designing and implementing scalable ML systems, while Data Scientists analyze data and build models. Both roles require advanced degrees and often overlap in skills, but their core responsibilities differ in scope and focus.

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

The top searched job categories for Remote Machine Learning Architect jobs in Leominster, MA are:

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

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

Remote Machine Learning Architect jobs near you

Data Scientist (Hybrid Worcester, MA or Remote)

thg

Worcester, MA • On-site, Remote

Full-time

Posted 10 days ago

Job description

Our Personal Lines team is currently seeking a Data Scientist in our Worcester, MA office on a hybrid arrangement or fully remote work location. This is a full-time, exempt role.

Join a Team Where Data Drives Strategy:

At The Hanover, data science is a key driver of how we understand risk, improve customer experiences, and make smarter business decisions. We're looking for a curious, analytical, and collaborative Data Scientist to join our Personal Lines Analytics team.

In this role, you'll apply advanced analytics, machine learning, and statistical modeling techniques to solve meaningful business challenges across our Personal Lines organization. You'll work alongside business leaders, product managers, actuaries, and data scientists to transform complex data into actionable insights that influence underwriting, pricing, customer experience, and growth strategies.

This is an opportunity to work with large and complex datasets, develop production-ready analytical solutions, and help shape the future of a data-driven insurance organization.

Why Join The Hanover?

  • Work on high-impact analytics projects that directly influence business strategy and outcomes.
  • Partner with experienced data scientists, actuaries, and business leaders across the organization.
  • Access large-scale datasets and real-world business challenges that offer meaningful analytical opportunities.
  • Grow your technical and business skills while developing expertise in predictive analytics and machine learning.
  • Be part of a collaborative team that values innovation, continuous learning, and knowledge sharing.
  • Help modernize how a leading insurance organization uses data to serve customers and manage risk.

 

IN THIS ROLE, YOU WILL:

  • Develop and deploy predictive models, machine learning solutions, and statistical analyses to solve business problems.
  • Explore large datasets to identify patterns, trends, opportunities, and risks that drive business performance.
  • Partner with Personal Lines leaders and cross-functional stakeholders to understand business objectives and translate them into analytic solutions.
  • Design experiments, conduct exploratory analyses, and evaluate model performance to generate actionable insights.
  • Research and apply emerging data science methods, tools, and technologies to enhance business outcomes.
  • Communicate findings and recommendations through compelling visualizations, presentations, and storytelling tailored to technical and non-technical audiences.
  • Collaborate with data engineers and analytics partners to develop scalable, efficient, and sustainable analytical solutions.
  • Contribute to a culture of continuous learning, innovation, and analytical excellence.

 

WHAT YOU NEED TO APPLY:

Required Qualifications

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Economics, or a related quantitative field.
  • 2-6 years of experience applying data science, machine learning, advanced analytics, or statistical modeling in a business environment.
  • Experience using Python and/or R for data analysis and model development.
  • Strong foundation in statistical analysis, predictive modeling, machine learning, and data mining techniques.
  • Experience working with large datasets and relational databases.
  • Ability to translate business questions into analytical approaches and communicate results effectively.
  • Strong problem-solving skills and intellectual curiosity.

Preferred Qualifications

  • Master's degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field.
  • Experience building and deploying machine learning models in production environments.
  • Familiarity with cloud-based analytics platforms and modern data science workflows.
  • Insurance, financial services, or other risk-based industry experience.
  • Experience with data visualization and storytelling tools.

This job posting provides cursory examples of some of the job duties associated with this position. The examples provided are not complete, and the position may entail other essential and job-related functions and responsibilities that employees will be required to perform. 

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