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Research Machine Learning Federated Learning Jobs in New York

Jane Street

Machine Learning Researcher

New York, NY · On-site

... at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled ... At Jane Street, the lines between research, technology, and trading are intentionally blurry, and ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to ...

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or related fields. * Demonstrated experience working in cross-functional teams bridging ML research with ...

New York University

POSTDOCTORAL ASSOCIATE

New York, NY · On-site

$62K - $67K/yr

Conducting advanced research in machine learning and data analytics for power system operation and ... Federated learning * Multimodal machine learning * Large language models * Power system ...

Forhyre

Machine Learning Engineer

New York, NY

Research and implement appropriate ML algorithms and tools * Develop machine learning applications according to requirements * Select appropriate datasets and data representation methods * Run ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... Intellectual curiosity and excitement about state-of-the-art research across many ML problem ...

6AM City, LLC

Machine Learning Engineer

Manhattan, NY · On-site

$90 - $130/hr

Research and implement appropriate ML algorithms and tools * Develop machine learning applications according to requirements * Select appropriate datasets and data representation methods * Run ...

New York Times

Machine Learning Engineer

Manhattan, NY · On-site

$170.17 - $255.26/hr

S. or equivalent) in Engineering (any), Computer Science, Operations Research, Mathematics, Physics or a related field * At least 2 years of experience in Machine Learning or a related role * At ...

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

Machine Learning Researcher

Jane Street

New York, NY • On-site

Full-time

Re-posted 27 days ago

Job description

About the Position
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled educational experience. You'll work side by side with experienced ML Researchers on projects that we've selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.
At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you'll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. Trading poses unusual challenges-large models and nonstationary datasets in a competitive multi-agent environment-that force us to search for novel techniques.
You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored dataset, try a new modeling paradigm for a thorny problem, or consider blue-sky approaches that we're still trying to figure out. The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes.
Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication.
About You
If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. We're more interested in how you think and learn than what you currently know. You should be:
  • An undergraduate, PhD student, or postdoc with practical experience working on ML problems
  • Interested in applying logical and mathematical thinking to all kinds of problems
  • Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn from many problem domains
  • Fluent with a versatile set of models and tricks
  • Able to rapidly implement and iterate on your ideas in Python and your favorite ML framework
  • Eager to ask questions, admit mistakes, and learn new things

If you'd like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street's internship program here.

Apply