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Research Machine Learning Federated Learning Jobs in Sharon, MA

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Help us bridge machine learning research and real-world deployment! MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

Neurable, INC

Machine Learning

Cambridge, MA · On-site

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

Neurable, INC

Machine Learning

Cambridge, MA

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Sharon, MA

Research Machine Learning Federated Learning information

See Sharon, MA salary details

$26.9K

$44.9K

$92.8K

How much do research machine learning federated learning jobs pay per year?

As of Jul 28, 2026, the average yearly pay for research machine learning federated learning in Sharon, MA is $44,890.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,300.00 and $48,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is a Researcher in Machine Learning Federated Learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What job categories do people searching Research Machine Learning Federated Learning jobs in Sharon, MA look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Sharon, MA are:
What cities near Sharon, MA are hiring for Research Machine Learning Federated Learning jobs? Cities near Sharon, MA with the most Research Machine Learning Federated Learning job openings:
Research Machine Learning Federated Learning jobs near you
Infographic showing various Research Machine Learning Federated Learning job openings in Sharon, MA as of July 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $44,890 per year, or $21.6 per hour.
Machine Learning Engineer

Machine Learning Engineer

MatrixSpace

Burlington, MA • Remote

$165K - $200K/yr

Full-time

Posted 19 days ago

Job description

Help us bridge machine learning research and real-world deployment!

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.
We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new algorithms and implementing them in performant, maintainable, and scalable production systems. You'll also help build the ML infrastructure and tooling that accelerates future research, while ensuring our AI solutions are reliable enough for real-world deployment.

If you're technically curious, highly collaborative, and motivated by solving complex real-world problems, we'd love to talk.

What You'll Do

  • Partner with Data Scientists to transform research algorithms into robust, production-quality software.
  • Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
  • Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
  • Design and implement AI agents, agentic workflows, and LLM-powered applications.
  • Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
  • Collaborate across engineering and research teams to transition prototypes into production systems.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.'

This is NOT a fully remote position!

Required

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
  • Strong hands-on programming experience in C++ and Python.
  • 3-5 years of experience developing and deploying machine learning systems in production environments.
  • Experience building AI agents, LLM-based applications, or intelligent automation systems.
  • Strong problem-solving skills and ability to work across the full development lifecycle.
  • Excellent written and verbal communication and collaboration skills.

Someone Who Will Thrive in This Role

  • Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
  • Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.
  • Takes ownership and drives projects from concept through production.
  • Continuously explores new AI, ML, and agentic technologies.
  • Works effectively across multidisciplinary teams.
  • Balances research innovation with practical product delivery.
  • Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Bonus Points

  • Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
  • Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
  • Experience optimizing models for edge deployment usingTensorRT, ONNX,OpenVINO, TVM, or similar tools.
  • Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
  • Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real-world capability. This is an engineering-heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.