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Research Machine Learning Federated Learning Jobs

webAI

AI Research Scientist

Austin, TX · On-site

Responsibilities : • Design, train, and optimize machine learning models including LLMs ... federated learning • Experience contributing to academic publications, patents, or open-source ML ...

Centific

Technical Intern

$40/hr

... Machine Learning, and more? We're thrilled to announce our PhD Research Internship Program, where ... Learning - Federated Learning / Differential Privacy - Red Teaming - ML Ops - LLM Ops ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The research intern will be in a fast-paced start-up environment playing a crucial technical role ...

HEB

Data Scientist - eCommerce

San Antonio, TX · On-site

$158K/yr

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

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Research Machine Learning Federated Learning information

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$25.5K

$42.6K

$88K

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

As of Jul 1, 2026, the average yearly pay for research machine learning federated learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 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.

More about Research Machine Learning Federated Learning jobs
What cities are hiring for Research Machine Learning Federated Learning jobs? Cities with the most Research Machine Learning Federated Learning job openings:
What states have the most Research Machine Learning Federated Learning jobs? States with the most job openings for Research Machine Learning Federated Learning jobs include:
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Research Machine Learning Federated Learning jobs near you
Infographic showing various Research Machine Learning Federated Learning job openings in the United States as of June 2026, with employment types broken down into 20% As Needed, 60% Part Time, and 20% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Assistant Member Tenure-earning in the Department of Machine Learning at Moffitt Cancer Center

Assistant Member Tenure-earning in the Department of Machine Learning at Moffitt Cancer Center

Moffitt

Chicago, IL • On-site

$17.50 - $20.50/hr

Full-time

Posted 8 days ago

Job description

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer.As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Join a dedicated team of nearly 11,000 who are shaping the future we envision. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and is continually named one of the Tampa Bay Times' Top Workplaces.

Summary

The faculty member will develop and maintain an active research program. The faculty member will support his/her research primarily through extramural grants and publish original research reports in peer-reviewed scientific journals. The faculty member will recruit and appropriately mentor research personnel within his/her research program. The faculty member will actively and collegially participate in the CCSG programs and the Moffitt Research Institute activities.The Independent Scientist Pathway is intended for tenure-track individuals who dedicate most of their effort to independent research. A portion of their effort is dedicated to educating future investigators, by teaching graduate students and medical students, and supervising postdoctoral fellows. These individuals will have their primary appointment in a Basic Science or Population Science department. They may have a secondary appointment in a Clinical Science departmentComprehensive Benefit Package | Relocation Assistance | Start-Up Package & Research Incentive Plan The Department of Machine Learning (ML) at Moffitt Cancer Center, a National Cancer Institute-designated Comprehensive Cancer Center, is seeking a new faculty member in the tenure-earning rank of Assistant Member with research interests in artificial intelligence, decision support systems, machine and deep learning, federated learning, and their application in cancer discovery and clinical care. The new faculty will join an expanding ML Department. We currently have faculty initiating a wide range of machine learning research and its application in oncology in collaboration with other members of the Quantitative Science Division, including the Biostatistics and Bioinformatics Department and the Integrated Mathematical Oncology Department, as well as with other research and clinical departments within the cancer center. Moffitt Cancer Center is characterized by a culture of collegiality and team science, facilitating cross-disciplinary collaborations for cancer research and mentoring. Faculty development is a tenet of Moffitt culture and an essential part of this department's philosophy to develop future leaders in the emerging field of machine learning in oncology. Position Highlights: Access to extensive retrospective and prospective data for real-world predictive analytics, and other clinical research resources, including an integrated repository of clinical, genomic, imaging, and patient-reported information as well as biospecimens from a large cohort of patients. Collaboration with implementation scientists offers the opportunity to integrate machine learning algorithms into the electronic medical record and clinic workflows to improve clinical care. Access to Moffitt's extensive computational and rich data resources such as the ML Department features state-of-the-art DGX-A100/DGX-H100/DGX-H200 cluster and machine learning engineers for advanced machine learning applications with retrospective and prospective comprehensive clinical datasets, with a focus on data integration and personalized cancer care. The Ideal Candidate: Expertise in artificial intelligence, decision support systems, machine and, deep learning, federated learning, who are interested in applying this expertise to cancer research and translational oncology. Preference will be given to applicants with an outstanding record conducting team science or collaborative research with an emphasis on machine learning in healthcare. Areas of interest include: the applications of deep learning, federated learning, explainability and interpretability of machine learning in outcome modeling, human-machine interaction, clinical decision support, and information retrieval. Demonstrate experience (or potential) as a collaborative or independent researcher with extramurally funded research studies, presentations at national and international conferences, and a record of high-quality peer-reviewed publications. Responsibilities: Maintain a productive integrated and/or independent research program in machine learning in oncology. Collaborate on a variety of machine learning research projects both within Moffitt and externally. Engage in educational (e.g., mentorship) and service activities across Moffitt and its affiliates (AI in cancer with USF). Contribute to current and initiate future machine learning applications at Moffitt, as evidenced by a history of peer-reviewed publications and involvement in grant-supported research projects. Ongoing research includes but is not limited to outcome modeling, human-machine interaction, clinical decision support, information retrieval, quantitative imaging (radiomics), digital pathology (pathomics), and computational biology, among others, where machine learning can accelerate cancer discovery and improve care delivery. Credentials and Qualifications: Doctorate degree in computer science, engineering, Physics, mathematics, statistics or a relevant field with appropriate research training and experience. Academic rank beyond Assistant Member will be commensurate with experience and qualifications. Moffitt is affiliated with the University of South Florida, and a University appointment is available in the rank of Assistant/Associate Professor as applicable in the appropriate departments. Moffitt-based faculty members focus their efforts on research, with minimal expectations for formal teaching. Tampa is a thriving metropolitan city that provides its residents with a high quality of life. The Tampa Bay area has become a hub for groundbreaking research, welcoming individuals from around the globe. This diverse city is engulfed with rich culture, year-round activities for all, beautiful beaches, amazing cuisine, and so much more. Questions regarding the position should be directed to: Issam El Naqa, PhD, FIEEE, Search Committee Chair, Department of Machine Learning (Issam.Elnaqa@moffitt.org).

Salary Range

Salary ranges posted for this position represent the expected base pay range for the role. Actual compensation may vary based on location and a variety of job-related factors, including experience, skills, education, and internal equity among Team Members in similar positions.


We are committed to maintaining fair and equitable pay practices and regularly review compensation to ensure alignment across our workforce.

Moffitt Career Site

If you have the vision, passion, and dedication to contribute to our mission,then we have a place for you!

1. Equal Employment Opportunity

Moffitt Cancer Center is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or protected veteran or disabled status. We seek candidates whose skills, and personal and professional experience, have prepared them to contribute to our commitment to diversity and excellence.

2. Reasonable Accommodation

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