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As of Sep 10, 2026, the average hourly pay for phd mathematics machine learning in the United States is $44.42, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $72.12 per hour, depending on experience, location, and employer.

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Infographic showing various Phd Mathematics Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $92,400 per year, or $44.4 per hour.

Machine Learning Specialist

New York, NY โ€ข On-site

Applied Physics
Pharmaceutical and Medicine Manufacturingย โ€ขย 1 - 10 employees

Full-time

Re-posted 25 days ago


Job description

Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields.

Responsibilities:

  • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
  • Implement, train, and validate proposed algorithms for specific problem domains.
  • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
  • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
  • Travel as required to coordinate research with collaborators and visit field sites.

Requirements

  • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
  • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
  • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
  • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
  • Proven ability to undertake original research and communicate findings in peer-reviewed publications.
  • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Benefits

We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world.

If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.