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Research Machine Learning Federated Learning Jobs in Philadelphia, PA

Varsity Tutors

Machine Learning Tutor

Chester, PA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

Varsity Tutors

Machine Learning Tutor

Trenton, NJ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Philadelphia, PA

Research Machine Learning Federated Learning information

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$25.7K

$43K

$88.8K

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

As of Aug 31, 2026, the average yearly pay for research machine learning federated learning in Philadelphia, PA is $42,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,800.00 and $46,400.00 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 are popular job titles related to Research Machine Learning Federated Learning jobs in Philadelphia, PA?

For Research Machine Learning Federated Learning jobs in Philadelphia, PA, the most frequently searched job titles are:

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

The top searched job categories for Research Machine Learning Federated Learning jobs in Philadelphia, PA are:

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Cities near Philadelphia, PA with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Machine Learning Researcher

Philadelphia, PA • On-site

Susquehanna International Group, LLP
Finance and Insurance • 1 - 5K employees
Learn more about Susquehanna International Group, LLPexternal

Full-time

Re-posted 3 days ago

Job description

Overview
Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.
We're looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.
What you'll do
  • Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • Develop automation tools to streamline research and system development
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Partner with engineering teams to implement and test models in production environments

What we're looking for
  • PhD in computer science, machine learning, mathematics, physics, statistics, or a related field
  • Strong track record of applying ML in academic or industry settings, with 5+ years of experience building impactful deep learning systems
  • A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Strong programming skills in Python and/or C++
  • Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments
  • Hands-on experience applying deep learning on time series data
  • Strong foundation in mathematics, statistics, and algorithm design
  • Excellent problem-solving skills with a creative, research-driven mindset
  • Demonstrated ability to work collaboratively in team-oriented environments
  • A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
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