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Physics Based Machine Learning Jobs in New York (NOW HIRING)

Microsoft AI

Machine Learning

Manhattan, NY · On-site

... Physics, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying machine learning techniques and driving product direction). Company

PhysicsX

Machine Learning Engineer

New York, NY · On-site

By enabling high-fidelity, multi-physics simulation through AI inference across the entire ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

Autodesk

Machine Learning Engineering Manager

New York, NY · On-site

$148K - $266K/yr

... based solutions, and advanced 3D modeling and graphics. This innovation is happening across our ... Create processes that make gathering and processing large batches of geometry, physics, and design ...

Photonium

Founding ML Engineer

Manhattan, NY

Founding Machine Learning Engineer This is a full-time on-site role for a Founding Machine Learning ... ML pipelines. • Interest in optics, physics-based simulation, or generative design. • ...

Purple Drive

Machine Learning Engineer

Newark, NJ

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in ... Hands-on experience with Generative AI , LangChain, and RAG-based techniques. * Expertise in ML/DL ...

GPTZero

Machine Learning Intern

New York, NY · On-site

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... We use AI-based tools (such as Endorsed.ai and Juicebox.ai) to help us to accelerate candidates at ...

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Physics Based Machine Learning information

What types of projects or problems does a Physics Based Machine Learning professional typically work on?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.

What is a Physics Based Machine Learning job?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

What are the key skills and qualifications needed to thrive in the Physics Based Machine Learning position, and why are they important?

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What are popular job titles related to Physics Based Machine Learning jobs in New York? For Physics Based Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Physics Based Machine Learning jobs in New York look for? The top searched job categories for Physics Based Machine Learning jobs in New York are:
What cities in New York are hiring for Physics Based Machine Learning jobs? Cities in New York with the most Physics Based Machine Learning job openings:
Physics Based Machine Learning jobs near you
Infographic showing various Physics Based Machine Learning job openings in New York as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Temporary. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution.
Machine Learning Specialist

Machine Learning Specialist

Applied Physics

New York, NY • On-site

Full-time

Posted 28 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.

Apply