ZipRecruiter

Log In

1

Research Machine Learning Federated Learning Jobs in Sharon, MA

Socket.dev

Machine Learning Research Engineer

Cambridge, MA · On-site

$120 - $192.50/hr

The Role FL105 seeks a talented Machine Learning Research Engineer . The successful candidate will innovate, develop and apply machine learning (ML) methods to create foundational psychological tools.

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 ...

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 ...

next page

Showing results 1-20

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 Aug 20, 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 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 are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

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 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 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.

Research Engineer, Machine Learning

Basis Research Institute

Cambridge, MA • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Basis Research Institute is a nonprofit applied AI research organization focused on understanding and building intelligence. They are seeking a Research Engineer specializing in Machine Learning to translate research ideas into high-quality code while engaging in programming language design and contributing to the organization's culture.
Responsibilities:
• Translate research ideas into correct, robust, and scalable high-quality code.
• Engage in programming language design/implementation.
• Performance engineering, scaling research code.
• Algorithm development.
• Contribute to the culture and direction of Basis.
• (Optionally) Publish and present findings in journals and conferences.
Qualifications:
Required:
• Possess excellent programming and software engineering skills, especially in Julia, Python, C++, ML-family languages.
• Have demonstrated the ability to drive software projects from start to finish. This could be evidenced by open-source projects, technical reports, and publications.
• Be comfortable digesting research from PL and/or ML venues, such as PLDI, POPL, NeurIPS, or ICML.
• Progress with a high degree of autonomy and under uncertainty.
• Be enthusiastic about solving real-world problems and making a positive societal impact.
• Have demonstrated significant technical achievements within ML engineering. Examples include: You've implemented variants of newly published techniques from scratch. You've built systems and workflows for training large models distributed across many machines. You've built systems that span all levels of the programming stack from high-level API infrastructure to close-to-the-metal code.
Preferred:
• A PhD (or equivalent experience) in technical areas including: statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, mathematics.
Company:
Basis is a nonprofit applied research organization with two mutually reinforcing goals. The first is to understand and build intelligence. Founded in 2022, the company is headquartered in New York, USA, with a team of 11-50 employees. The company is currently Early Stage.

Apply