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Research Machine Learning Federated Learning Jobs in Queens, NY

Qualcomm

Machine Learning Compiler

Manhattan, NY · On-site

$141 - $211/hr

As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art ...

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 ...

Vibepilot

Machine Learning Researcher

Manhattan, NY · On-site

$120 - $180/hr

# Machine Learning ResearcherApply For This Role## About The RoleThe Machine Learning Researcher will ... Research and develop novel ML models for logistics optimisation and predictive analytics.* Deploy ...

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 ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Queens, NY

Research Machine Learning Federated Learning information

See Queens, NY salary details

$26.6K

$44.4K

$91.8K

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

As of Aug 29, 2026, the average yearly pay for research machine learning federated learning in Queens, NY is $44,435.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,900.00 and $48,000.00 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 Queens, NY?

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

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

The top searched job categories for Research Machine Learning Federated Learning jobs in Queens, NY are:

What cities near Queens, NY are hiring for Research Machine Learning Federated Learning jobs?

Cities near Queens, NY with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Research Engineer, Machine Learning

New York, NY • On-site

Basis Research
See more jobs at Basis Researchexternal

$120K - $180K/yr

Full-time

Re-posted 13 days ago

Job description

About Basis
Basis is a nonprofit applied AI research organization with two mutually reinforcing goals.
The first is to understand and build intelligence. This means to establish the mathematical principles of what it means to reason, to learn, to make decisions, to understand, and to explain; and to construct software that implements these principles.
The second is to advance society's ability to solve intractable problems. This means expanding the scale, complexity, and breadth of problems that we can solve today, and even more importantly, accelerating our ability to solve problems in the future.
To achieve these goals, we're building both a new technological foundation that draws inspiration from how humans reason, and a new kind of collaborative organization that puts human values first.
About the Role
Research engineers support Basis' mission by translating research ideas into correct, robust, and scalable high-quality code.
We seek individuals who excel technically and value probing concepts at their foundations. Our research engineers aspire to conduct rigorous, high-quality, robust science, unafraid to tinker, make mistakes, and explore radically different ideas to achieve this.
Basis is a collaborative endeavor, both internally and with our external partners; we seek individuals who relish working with others on challenges larger than those they can tackle alone.
Machine Learning Research Engineers
This role targets experts in machine learning engineering. The core areas of ML research engineering include:
  • Probabilistic programming and statistical inference
  • Deep learning
  • Causal inference
  • Program synthesis and analysis
  • ML Ops and systems engineering

These areas are honed within the context of building reasoning systems. Consequently, research engineers will also engage with topics such as programming language design and implementation, automatic differentiation, and SAT/SMT solvers, among others.
We expect you to:
  • Possess excellent programming and software engineering skills, especially in Julia, Python, C++, ML-family languages.
  • Have demonstrated the ability to drive software projects from start to finish. This could be evidenced by open-source projects, technical reports, and publications.
  • Be comfortable digesting research from PL and/or ML venues, such as PLDI, POPL, NeurIPS, or ICML.
  • Progress with a high degree of autonomy and under uncertainty.
  • Be enthusiastic about solving real-world problems and making a positive societal impact.
  • Have demonstrated significant technical achievements within ML engineering. Examples include:
    • You've implemented variants of newly published techniques from scratch.
    • You built systems and workflows for training large models distributed across many machines.
    • You've built systems that span all levels of the programming stack from high-level API infrastructure to close-to-the-metal code.

In addition, the following would be an advantage:
  • A PhD (or equivalent experience) in technical areas including: statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, mathematics.

Responsibilities:
  • Translate research ideas into correct, robust, and scalable high-quality code.
  • Engage in programming language design/implementation.
  • Performance engineering, scaling research code.
  • Algorithm development.
  • Contribute to the culture and direction of Basis.
  • (Optionally) Publish and present findings in journals and conferences.
Role Details
Exceptional candidates who may not meet all of the following criteria are still encouraged to apply.
  • FT/PT: This is a full-time position
  • Hours: While we prioritize in-person collaboration for its benefits to creative work, there is a degree of flexibility in your working hours. Be prepared to attend multi-day Basis-wide in-person events.
  • Location: This role is in-person in either New York City or Boston.
  • Salary range: Competitive salary and bonuses

Non-Discrimination Notice
Basis Research Institute provides equal employment opportunities without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or genetics and prohibits discrimination based on all protected characteristics.
Privacy Notice
By submitting your application, you grant Basis permission to use your materials for both hiring evaluation and recruitment-related research and development purposes. Your information may be processed in different countries, including the US. You retain copyright while providing Basis a license to use these materials for the stated purposes.
Read our full Global Data Privacy Notice here.

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