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Research Machine Learning Federated Learning Jobs in New York

Strivector Corp

Machine Learning

Manhattan, NY · On-site

They are seeking a Machine Learning professional capable of tackling research problems with commercial applications, applying technical expertise to real-world financial and operational challenges.

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$224K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine ...

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$200K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine ...

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within ... Conduct empirical ML research across multiple problem domains, rapidly prototyping and iterating ...

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within ... Conduct empirical ML research across multiple problem domains, rapidly prototyping and iterating ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in New York

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 / Machine Learning Engineer

Anson McCade

Manhattan, NY • On-site

$200K/yr

Full-time

Posted 23 days ago

Job description

$200,000 - 2,000,000 USD
Onsite WORKING
Location: New York, New York - United States Type: Permanent
ML Researcher / ML Engineer
I am working with one of the world's leading quantitative trading firms, recognised for combining cutting-edge technology, quantitative research, and machine learning to solve some of the most complex challenges in global financial markets. Renowned for its research-driven culture and engineering excellence, the firm continues to make significant investments in next-generation machine learning capabilities that directly enhance trading performance and business outcomes.
As part of the continued expansion of its Machine Learning platform, the firm is looking to hire exceptional Machine Learning Researchers and Machine Learning Engineers to join several high-performing teams working across large-scale machine learning, deep learning, distributed systems, and production ML infrastructure.
The Opportunity
This is an opportunity to work alongside some of the industry's leading researchers and engineers, developing advanced AI models and production-scale machine learning systems that are deployed directly into live trading environments.
Depending on your experience and interests, you may focus on areas including:
  • Large Language Models (LLMs)
  • Foundation model training and optimisation
  • Agentic AI systems
  • Applied machine learning research
  • Model evaluation and post-training optimisation
  • Distributed systems and AI infrastructure
You'll tackle challenging mathematical and engineering problems while building scalable, production-ready AI solutions in a highly collaborative and research-driven environment.
Requirements
Successful candidates will typically possess:
  • Strong experience in Machine Learning, Deep Learning, Large Language Models, AI Infrastructure, or Distributed Systems
  • Excellent programming skills in Python and/or C++
  • Experience developing and deploying production-grade machine learning systems
  • A strong mathematical foundation and exceptional problem-solving ability
  • A passion for solving technically demanding challenges in a fast-paced environment
Why Join?
This firm offers the opportunity to work on some of the most advanced AI and machine learning challenges in the financial industry, alongside world-class researchers, engineers, and quantitative professionals.
The compensation package is exceptionally competitive, with top performers receiving industry-leading total compensation, complemented by outstanding career progression, access to cutting-edge technology, and the opportunity to make a direct impact on live trading systems from day one.

Apply