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Machine Learning Postdoc Jobs in New York (NOW HIRING)

Jane Street

Machine Learning Researcher

New York, NY · On-site

An undergraduate, PhD student, or postdoc with practical experience working on ML problems ... Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

An undergraduate, PhD student, or postdoc with practical experience working on ML problems ... Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn ...

New York University

POSTDOCTORAL ASSOCIATE

New York, NY · On-site

$62K - $67K/yr

Description POSTDOCTORAL ASSOCIATE New York University Tandon School of Engineering NYU Tandon ... Conducting advanced research in machine learning and data analytics for power system operation and ...

New York University

POSTDOCTORAL ASSOCIATE

New York, NY · On-site

$65K/yr

Description POSTDOCTORAL ASSOCIATE New York University Tandon School of Engineering The Department ... The successful candidate will have a demonstrated background in machine learning, physical ...

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Machine Learning Postdoc information

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$24.1K

$124.6K

$234.5K

How much do machine learning postdoc jobs pay per year?

As of Sep 8, 2026, the average yearly pay for machine learning postdoc in New York is $124,629.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,409.00 and $171,643.00 per year, depending on experience, location, and employer.

What is a machine learning postdoc?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a machine learning postdoc?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

What are the key skills and qualifications needed to thrive in a machine learning postdoc position?

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What are the most commonly searched types of Machine Learning Postdoc jobs in New York?

The most popular types of Machine Learning Postdoc jobs in New York are:

What are popular job titles related to Machine Learning Postdoc jobs in New York?

For Machine Learning Postdoc jobs in New York, the most frequently searched job titles are:

What job categories do people searching Machine Learning Postdoc jobs in New York look for?

The top searched job categories for Machine Learning Postdoc jobs in New York are:

What cities in New York are hiring for Machine Learning Postdoc jobs?

Cities in New York with the most Machine Learning Postdoc job openings:

Machine Learning Postdoc jobs near you
Infographic showing various Machine Learning Postdoc job openings in New York as of September 2026, with employment types broken down into 100% Full Time. Highlights an 81% In-person, 9% Hybrid, and 10% Remote job distribution, with an average salary of $124,629 per year, or $59.9 per hour.

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