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Machine Learning Researcher Jobs in New York (NOW HIRING)

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.

Morgan Stanley's Machine Learning Research Department is dedicated to solving mission-critical problems across various business units and technology teams. They are seeking a candidate who can tackle ...

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.

Machine Learning Researcher

New York, NY ยท On-site

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within a results-oriented, agile organization. This role offers the rare combination of intellectual ...

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

Machine Learning Researcher

New York, NY ยท On-site

$200K - $350K/yr

As a Machine Learning Engineer at Extend, you'll be responsible for building state-of-the-art ... in AI research, push for real-world customer impact (not only theory), and are excited about ...

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.

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Machine Learning Researcher information

See New York salary details

$32.8K

$123.7K

$180K

How much do machine learning researcher jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning researcher in New York is $123,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,300.00 and $168,500.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Researchers face when transitioning from academic research to industry roles?

Machine Learning Researchers often find that transitioning to industry involves adapting to faster project timelines, collaborative workflows, and a focus on scalable, real-world solutions rather than theoretical advances alone. In industry, you'll likely work closely with cross-functional teams, such as software engineers and product managers, to ensure models are both practical and maintainable. Balancing innovation with business objectives, handling production constraints, and communicating complex findings to non-technical stakeholders are some of the key challenges you may encounter.

What are the key skills and qualifications needed to thrive as a Machine Learning Researcher, and why are they important?

To thrive as a Machine Learning Researcher, you need deep expertise in mathematics, statistics, programming (typically Python), and a strong academic background in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch and experience with tools for data analysis and model development are standard, often supported by advanced degrees or relevant certifications. Critical thinking, creativity, and effective communication are vital soft skills for developing novel solutions and collaborating across interdisciplinary teams. These skills enable researchers to design innovative algorithms, validate models rigorously, and contribute impactful advancements in the field.

What is the difference between Machine Learning Researcher vs Data Scientist?

AspectMachine Learning ResearcherData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceDegree in CS, statistics, or related; strong analytical skills
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, consulting
Employer & Industry UsageUniversities, research institutions, tech firmsCorporations, startups, finance, healthcare
Common Search & ComparisonFocus on theoretical ML advancementsFocus on data analysis & business insights

While both roles involve working with data and algorithms, Machine Learning Researchers primarily focus on developing new algorithms and advancing ML theory, often in research or academic settings. Data Scientists apply these techniques to analyze data, generate insights, and support business decisions in industry environments.

What does a Machine Learning Researcher do?

A Machine Learning Researcher designs, develops, and tests algorithms and models that allow computers to learn from and make decisions based on data. They often work on advancing the field by exploring new methods, improving existing algorithms, and publishing their findings. These researchers collaborate with engineers and data scientists to apply their research to practical problems in areas like computer vision, natural language processing, and robotics. Their work typically involves a combination of mathematics, statistics, programming, and experimentation.
What are the most commonly searched types of Machine Learning Researcher jobs in New York? The most popular types of Machine Learning Researcher jobs in New York are:
Infographic showing various Machine Learning Researcher job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $123,737 per year, or $59.5 per hour.
Machine Learning Researcher

Machine Learning Researcher

Jane Street

New York, NY โ€ข On-site

Other

Posted 11 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 tricksย 
  • 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.