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Research Machine Learning Federated Learning Jobs in Frederick, MD

Axle

Assistant Director of AI and Data

Rockville, MD · On-site

... Federated Learning. • Democratization of AI: Democratize access to AI tools within the client ... non-technical NIH researchers to utilize advanced analytics independently. Qualifications

Axle

Director of Data Solutions

Rockville, MD · On-site

... research, biomedical informatics, and data science applications. The Director of Data Solutions is ... federated learning/inference) and/or sensitive data platforms. • Experience leading simulation ...

Axle

Director of Data Solutions

Rockville, MD · On-site

Axle is a bioscience and information technology company specializing in translational research ... federated learning/inference) and/or sensitive data platforms. • Experience leading simulation ...

Axle

Associate Director of AI and Data

Rockville, MD · On-site

... research, biomedical informatics, and data science applications. They are seeking an Associate ... Federated Learning. • Democratize access to AI tools within the client environment. • Lead ...

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Showing results 21-40

All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Frederick, MD

Research Machine Learning Federated Learning information

See Frederick, MD salary details

$25.4K

$42.3K

$87.5K

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

As of Aug 17, 2026, the average yearly pay for research machine learning federated learning in Frederick, MD is $42,340.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 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?

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 Frederick, MD?

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What job categories do people searching Research Machine Learning Federated Learning jobs in Frederick, MD look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Frederick, MD are:

What cities near Frederick, MD are hiring for Research Machine Learning Federated Learning jobs?

Cities near Frederick, MD with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Research Scientist Intern (2025)

Whiterabbit.ai

Frederick, MD • On-site

Other

Re-posted 26 days ago

Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity

Apply