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Physics Informed Machine Learning Jobs in Queens, NY

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 ...

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:

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:

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:

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ... rules of physics. Meta is proud to be an Equal Employment Opportunity and Affirmative Action ...

Senior Staff Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

MS/PhD in a quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics or other technical field) or equivalent experience * 8+ years building and shipping machine learning ...

New

Senior Staff Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

MS/PhD in a quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics or other technical field) or equivalent experience * 8+ years building and shipping machine learning ...

New

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Physics Informed Machine Learning information

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

As of Aug 9, 2026, the average hourly pay for physics informed machine learning in Queens, NY is $20.94, according to ZipRecruiter salary data. Most workers in this role earn between $13.03 and $26.59 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?

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 Queens, NY? For Physics Informed Machine Learning jobs in Queens, NY, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Queens, NY look for? The top searched job categories for Physics Informed Machine Learning jobs in Queens, NY are:
What cities near Queens, NY are hiring for Physics Informed Machine Learning jobs? Cities near Queens, NY with the most Physics Informed Machine Learning job openings:

Senior Machine Learning Engineer

PhysicsX

New York, NY • On-site

$114K - $157K/yr

Full-time

Retirement, PTO

Re-posted 21 days ago


Job description

About us
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
Who We're Looking For
As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
Note: This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.
This Role
As a Senior MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.
You'll:
  • Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) to customer production environments.
  • Communicate results and trade-offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
  • Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
  • Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
  • Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision-making under pressure.
  • Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
  • Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

As a senior member of the team, you'll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you'll contribute to this exciting journey!
What we offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn't stop there ...
Equity options - share meaningfully in the company you're helping to build.
5% contribution to 401(k) - build long-term security with a strong retirement plan.
Free team lunch 1x/week - good food, great company, and space to connect.
Private health insurance - comprehensive cover for you, offering total peace of mind.
Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
Personal development - dedicated support for learning, development, and leveling up over time.
Gympass / Wellhub (subsidized) - for you and up to 3 family members, supporting both physical and mental wellbeing.
Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses.
Watch this space, we're continuing to build this as we grow...
Salary range:
$200,000 - $250,000 depending on experience
Seniority will be assessed throughout our interview process
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.