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Physics Informed Machine Learning Jobs in Newark, NJ

Siemens

Principal Applied Scientist

New York, NY · On-site

$197K - $267K/yr

The work sits at the intersection of machine learning research, real world data, and production ... Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML ...

Wonder

Senior Machine Learning Engineer

Manhattan, NY

$176K - $191K/yr

MS/PhD in quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics or ... machine learning, or related field * 2+ years experience in applied predictive modeling with ...

New

Siemens

Senior Applied Scientist

New York, NY · On-site

$167K - $226K/yr

The work sits at the intersection of machine learning research, real world data, and production ... Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML ...

Optimum

Sr Machine Learning Engineer

Long Island City, NY · On-site

$113K - $155K/yr

Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems ... Physics, Biology, Chemistry or Engineering. An advanced degree, Data Science bootcamp or MOOC ...

Optimum

Sr Machine Learning Engineer

Long Island City, NY · On-site

$113K - $155K/yr

Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems ... Physics, Biology, Chemistry or Engineering. An advanced degree, Data Science bootcamp or MOOC ...

Applied Physics

Data Scientist

New York, NY · On-site

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... analysis, machine learning, information visualization, as well as others. Responsibilities:

PhysicsX

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

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

Siemens

Applied Scientist

New York, NY · On-site

$182K - $216K/yr

The work sits at the intersection of machine learning research, real world data, and production ... Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML ...

Applied Physics

Data Scientist

New York, NY

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... analysis, machine learning, information visualization, as well as others. Responsibilities:

Mercor

Senior Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Civil Engineering , Physics , Chemistry , Mathematics , Materials Science , or other STEM ...

Nexxen

Senior Machine Learning Engineer

Manhattan, NY · On-site +1

$180K - $220K/yr

Stay safe and informed. The Sr. Machine Learning Engineer will join our Applied Data Science group, part of Nexxen DSP Software Development. In this hands-on role, you will work in close ...

Applied Physics

Data Scientist

New York, NY · On-site

Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join ... analysis, machine learning, information visualization, as well as others. Responsibilities:

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How much do physics informed machine learning jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for physics informed machine learning in Newark, NJ is $20.98, according to ZipRecruiter salary data. Most workers in this role earn between $13.08 and $26.63 per hour, depending on experience, location, and employer.

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

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Newark, NJ? For Physics Informed Machine Learning jobs in Newark, NJ, the most frequently searched job titles are:
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What cities near Newark, NJ are hiring for Physics Informed Machine Learning jobs? Cities near Newark, NJ with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Retrosynthesis Researcher, Machine Learning

Retrosynthesis Researcher, Machine Learning

Schrödinger

New York, NY • On-site

$120K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Job description

Schrödinger seeks a Retrosynthesis Researcher in Machine Learning (ML) to join us in our mission to transform the discovery of therapeutics and materials.
Schrödinger has pioneered a physics-based software platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is used by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Our multidisciplinary drug discovery team also leverages the software platform to advance collaborative programs and its own pipeline of novel therapeutics to address unmet medical needs.
As a member of our Machine Learning team, you'll work at the forefront of computational chemistry and AI, contributing to high-impact research with real-world applications in small molecule drug discovery and materials science.
Who will love this job:
  • An ML expert who has applied AI tools to chemical reaction prediction or retrosynthesis (e.g., reaction templates, template-free approaches) and understands organic synthesis and reaction mechanisms
  • An experienced user of cheminformatics tools (e.g., RDKit, Open Babel)
  • A proficient Python programmer who's familiar with ML tools like Pytorch, Tensorflow, and JAX
  • An excellent problem-solver who's comfortable working collaboratively in a multidisciplinary research environment

What you'll do:
  • Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic pathway prediction
  • Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions, and identify novel synthetic routes
  • Curate and manage reaction datasets from literature, patents, and proprietary sources to train and validate predictive models
  • Integrate retrosynthesis tools with cheminformatics platforms and molecular modeling software
  • Collaborate with synthetic chemists to experimentally validate predicted retrosynthetic routes and optimize laboratory workflows
  • Contribute to scholarly publications in high-impact journals and represent the research group in conferences and workshops

What you should have:
  • PhD in Chemistry, Computational Chemistry, Cheminformatics, or a related field
  • A solid publication record that demonstrates expertise in retrosynthesis algorithms and computational chemistry

We'd prefer to hire someone who has:
  • Familiarity with chemical reaction databases (e.g., Reaxys, USPTO, Pistachio)
  • Knowledge of computer-aided synthesis planning (CASP) tools and retrosynthetic analysis software (e.g., AiZynthFinder, ASKCOS, IBM RXN)
  • A background in graph-based learning, attention mechanisms, and transformer architectures applied to chemical data
  • Familiarity with reaction condition prediction and reaction yield optimization.
  • Experience with Schrödinger Suite and LiveDesign
  • Experience with de novo design and generative machine learning methods
  • Experience with cloud computing and/or high-performance computing (HPC) resources
  • Exposure to quantum chemistry (DFT) is a plus

Pay and perks:
Schrödinger understands it's people that make a company great. Because of this, we're prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have regular catered meals in the office, a company culture that is relaxed but engaged, and over a month of paid vacation time. Our Office Management team also plans a myriad of fun company-wide events. New York is home to our largest office, but we have teams all over the world. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces.
Estimated base salary range: $120,000 - $145,000. Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs. If you have any questions regarding the compensation for this role, do not hesitate to reach out to a member of our Strategic Growth team.
Sound exciting? Apply today and join us!
As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or any other protected characteristic. To us, "diversity" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.

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