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Research Machine Learning Federated Learning Jobs in Massachusetts

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.

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 ...

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Research Machine Learning Federated Learning information

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 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 are popular job titles related to Research Machine Learning Federated Learning jobs in Massachusetts? For Research Machine Learning Federated Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Research Machine Learning Federated Learning jobs in Massachusetts look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Research Machine Learning Federated Learning jobs? Cities in Massachusetts with the most Research Machine Learning Federated Learning job openings:
Research Machine Learning Federated Learning jobs near you

Machine Learning Research Engineer

Flagship Pioneering, Inc.

Cambridge, MA • On-site

Full-time

Medical, Retirement

Posted 12 days ago

Job description

The Company
FL105 is a privately held, early-stage company pioneering the use of artificial intelligence to transform human psychological fitness and wellbeing. We are creating a platform that empowers people to build a life they are proud of and fulfilled by.
FL105 is backed by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and builds companies that invent breakthrough technologies that transform the world. Flagship has created over 100 groundbreaking companies since 2000, including Moderna.
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. This position is ideal for someone with broad expertise in machine learning, reinforcement learning from human feedback, supervised fine tuning, and computational sciences who is looking to join a very dynamic and innovative environment and pioneer the next frontier of innovation, application, and human-ai interactions enabled by state-of-the-art models. A successful candidate should have a passion for building technologies that enable others to maximize their potential.
Working at FL105, you will have the opportunity to work with world-class scientists, engineers, and researchers who work on cutting-edge ai research and applications.
Key Responsibilities
  • Design, develop, and deploy ML-powered applications that leverage large language models (LLMs) to address complex challenges in wellbeing.
  • Collaborate with psychological experts and translate interdisciplinary insights into computational frameworks.
  • Help advance the state of the art in context engineering, agentic AI and learning from human feedback.
  • Build scalable pipelines for data collection, labeling, training, and deployment of LLM-based systems.
  • Support the integration of ML systems into real-world applications with measurable outcomes.
  • Communicate findings to a multi-disciplinary audience.

Professional Experience & Qualifications
  • Masters level (or above) experience in CS, ML, and AI is preferred, but can be relaxed for exceptional candidates.
  • Strong foundation in machine learning, deep learning, and natural language processing (NLP).
  • Publications at top ML / NLP venues such as NeurIPS, ICML, ACL and EMNLP are a bonus.
  • Proven experience deploying LLM-powered applications in production environments, including expertise in frameworks like PyTorch, vLLM, and LangGraph.
  • Proficiency in Python and tools for ML development, large-scale data pipelines and pre-processing, and standard evaluation protocols.
  • Self-motivated and comfortable working in ambiguous, fast-moving environments with evolving goals.
  • Excellent communication and presentation skills.
  • Must be able to think independently and work collaboratively.
  • Experience in a previous startup is a plus.

About Flagship Pioneering
Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.
Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.
At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.
We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.
Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.
The salary range for this role is $120,000 - $192,500. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. FL105 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL105's good faith estimate as of the date of publication and may be modified in the future.
Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.

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