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Research Federated Learning Jobs (NOW HIRING)

AVEVA

Distinguished ML Data Scientist

Boston, MA · On-site

$255.50K - $425.50K/yr

... federated learning, and AI governance best practices.Proficiency in Python, SQL, R and machine ... Strong ability to translate emerging research into practical solutions.Strong collaboration with ...

Leidos

Senior AI Security Researcher

Huntsville, AL · On-site

$112.80K - $154.70K/yr

Knowledge of federated learning or edge AI deployments for cyber-physical systems or operational ... Experience contributing to multi-disciplinary research teams and collaborating with technology ...

FEDERATED CO-OPS INC

Agronomy Intern

Albertville, MN · On-site

$15 - $16/hr

... Cooperator and Federated Agronomist with assigned Discovery Plot related research projects. * Present information to agronomy group at completion of project. * General field scouting with ...

Leidos

Senior AI Security Researcher

Huntsville, AL · On-site

$112.80K - $154.70K/yr

Knowledge of federated learning or edge AI deployments for cyber-physical systems or operational ... Experience contributing to multi-disciplinary research teams and collaborating with technology ...

FEDERATED CO-OPS INC

Agronomy Intern

Albertville, MN · On-site

$15 - $16/hr

... Cooperator and Federated Agronomist with assigned Discovery Plot related research projects. * Present information to agronomy group at completion of project. * General field scouting with ...

Netflix

OR · On-site

$388K - $558K/yr

About the team Our Research Data Products team is at the forefront of insights innovation. Our team ... Understanding of privacy-preserving techniques (e.g., encryption, federated learning, synthetic ...

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Research Federated Learning information

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$2.4K

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$7.7K

How much do research federated learning jobs pay per month?

As of May 29, 2026, the average monthly pay for research federated learning in the United States is $5,290.17, according to ZipRecruiter salary data. Most workers in this role earn between $3,000.00 and $7,500.00 per month, depending on experience, location, and employer.

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

To thrive as a Researcher in Federated Learning, you need a strong background in machine learning, distributed systems, and statistics, typically supported by an advanced degree in computer science or a related field. Familiarity with programming languages like Python, frameworks such as TensorFlow Federated, and experience with privacy-preserving algorithms are essential. Critical thinking, collaboration, and effective communication are key soft skills for designing experiments and sharing findings with peers. These competencies are vital for advancing privacy-aware AI solutions and producing impactful research in this rapidly evolving domain.

What are some common challenges faced by professionals working in Research Federated Learning, and how can they be addressed?

Professionals in Research Federated Learning often encounter challenges such as ensuring data privacy across distributed devices, managing non-iid (non-independent and identically distributed) data, and optimizing communication efficiency between clients and servers. Addressing these issues requires strong collaboration with cross-functional teams, including data engineers, security experts, and software developers, to develop robust protocols and algorithms. Staying updated with the latest research and participating in open-source collaborations can also help overcome technical hurdles and drive innovation in this rapidly evolving field.

What is a Researcher in Federated Learning?

A Researcher in Federated Learning is a professional who studies, develops, and improves federated learning algorithms and systems. Federated learning is a machine learning approach where data remains decentralized, allowing multiple devices or organizations to collaboratively train models without sharing raw data. These researchers focus on advancing privacy, efficiency, and performance in distributed AI systems. Their work often involves experimenting with new methods, publishing findings, and contributing to the growing field of privacy-preserving machine learning.

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

AspectResearch Federated LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm developmentBusiness environments, analytics teams; focus on data analysis and insights
Industry UsageAI research, privacy-preserving ML, distributed systemsBusiness intelligence, marketing, finance, healthcare

Research Federated Learning involves developing privacy-focused, distributed machine learning algorithms, often in research or specialized tech settings. Data Scientists analyze data to generate insights and support decision-making in various industries. While both roles require strong analytical skills, Research Federated Learning emphasizes algorithm development and privacy, whereas Data Scientists focus on data analysis and reporting.

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Research Federated Learning jobs near you
Infographic showing various Research Federated Learning job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 97% Full Time, and 2% Contract. Highlights an 98% Physical, and 2% Hybrid job distribution, with an average salary of $63,482 per year, or $30.5 per hour.

Distinguished ML Data Scientist

AVEVA

Boston, MA • On-site

$255.50K - $425.50K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

PositionDistinguished ML Data ScientistLocationSan Leandro, CA; Boston, MA; New York, NYEmployment TypeFull-timeSalary Range$255,500.00 - $425,500.00 (minimum and maximum compensation; final compensation can vary)Key ResponsibilitiesInvestigate and recommend algorithmic/data science solutions to industrial problems.Define and translate ambiguous concepts into well-defined questions, drive analysis of complex datasets for insights, and design data-driven experiments and incubations for emerging AI and ML technologies.Drive the design and architecture of scalable data infrastructure and analytics platforms.Collaborate with cross-functional teams to prototype, pilot and test ML-driven solutions.Contribute to scientific and technical publications on AI/ML research.Essential Requirements12+ years of experience in data science, advanced analytics, ML engineering, or equivalent industry experience with 4+ years in hands-on statistical modeling, machine learning, data pipelines, and experimental design.Master's degree in Computer Science, Data Science, Statistics or related technical field; Ph.D. preferred.Deep expertise in frontier and emerging AI, ML and data science techniques and best practices, including model evaluation, training/tuning, monitoring, and governance.Recent experience with modern AI paradigms such as world models, foundation models, and multi-modal language models; agent-based systems and orchestration; and context retrieval and augmentation techniques.Experience in responsible deployment practices, model drift mitigation, privacy-preserving federated learning, and AI governance best practices.Proficiency in Python, SQL, R and machine learning libraries.Exceptional communication and presentation skills and ability to articulate complex technical concepts to both technical and non-technical audiences.Desired Skills and CompetenciesExperience in industrial domains.Familiarity with cloud platforms (AWS, Azure, GCP).Experience mentoring junior team members and leading technical programs end-to-end.What Success Looks LikeCompelling storyteller who can use data to influence decisions.Ability to meaningfully influence AI roadmaps and technology direction through data-driven work.Strong ability to translate emerging research into practical solutions.Strong collaboration with cross-functional technical and non-technical teams.BenefitsUSA Benefits include: Flex work hours, 20 days PTO rising to 25 with service, three paid volunteering days, primary and secondary parental leave, well-being support, medical, dental, vision, and 401K.Equal OpportunityAVEVA is an Equal Opportunity Employer. We are committed to being an exemplary employer with an inclusive culture, developing a workplace environment where all our employees are treated with dignity and respect.

We value diversity and the expertise that people from different backgrounds bring to our business. AVEVA provides reasonable accommodation to applicants with disabilities where appropriate. If you need reasonable accommodation for any part of the application and hiring process, please notify your recruiter.

Determinations on requests for reasonable accommodation will be made on a case-by-case basis.All successful applicants must undergo drug screening and a comprehensive background check.J-18808-Ljbffr

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