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Physics Informed Machine Learning Jobs in Bronx, NY

New York University

Post Doctorate Associate

New York, NY · On-site

$70K/yr

... machine learning, and network-based infrastructure modeling. New York University (NYU) is one of ... The CERA Lab develops data-driven and physics-informed methods to identify, measure, and manage ...

Everstar Inc

Founding AI Engineer

New York, NY · On-site

Physics-informed design safety analyses using world models that reason about thermal hydraulics ... Agentic workflows that compound over time, learning from each regulatory submission to improve the ...

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 ...

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

As of Sep 7, 2026, the average hourly pay for physics informed machine learning in Bronx, NY is $20.90, according to ZipRecruiter salary data. Most workers in this role earn between $13.03 and $26.54 per hour, depending on experience, location, and employer.

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 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 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 popular job titles related to Physics Informed Machine Learning jobs in Bronx, NY?

For Physics Informed Machine Learning jobs in Bronx, NY, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Bronx, NY look for?

The top searched job categories for Physics Informed Machine Learning jobs in Bronx, NY are:

What cities near Bronx, NY are hiring for Physics Informed Machine Learning jobs?

Cities near Bronx, NY with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Bronx, NY as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $43,474 per year, or $20.9 per hour.

Machine Learning Engineer (Technical Leadership)

Meta

New York, NY • On-site

$271K/yr

Full-time

Posted 21 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 247 rated software companies

Job description

Meta is seeking a Machine Learning Engineer to join our integrity engineering team. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale, including model development, training infrastructure, and optimization. You will work on leveraging ML models to detect and enforce content to keep the platforms safe and create a better user experience across Meta's products — from payment fraud detection and click-through rate prediction to search ranking, content enforcement, and spam detection. This role involves applying advanced ML techniques to some of the most exciting and massive-scale prediction problems on the web.
Machine Learning Engineer (Technical Leadership) Responsibilities:
  • Drive the team's ML strategy & technical direction to pursue opportunities that advance machine learning capabilities across the organization
  • Design and develop end-to-end machine learning systems, from data pipelines to model training, evaluation, and deployment
  • Lead experimentation and A/B testing frameworks to measure and optimize model performance
  • Build highly scalable classifiers and ML tools leveraging deep learning, data regression, and rules-based models
  • Adapt and optimize machine learning methods for modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
  • Partner with research teams to translate cutting-edge ML research into production systems
  • Mentor and influence ML engineers across organizations, raising the bar for ML best practices
  • Identify new ML opportunities for the larger organization and influence staffing/prioritization of these initiatives
  • Effectively communicate complex ML systems and architectural decisions to technical and non-technical stakeholders

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience leading projects with industry-wide impact
  • Experience communicating and working across functions to drive solutions
  • Experience in mentoring/influencing engineers across organizations
  • Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term vision
  • Experience in driving large cross-functional/industry-wide engineering efforts
  • 12+ years of experience in programming languages (Python, C++, or Java) with technical background
  • 8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or deep learning based methods

Preferred Qualifications:
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Experience with deep learning frameworks (PyTorch, TensorFlow) and ML infrastructure tools
  • Familiarity with MLOps practices, model monitoring, and production ML systems
  • Experience building and optimizing large-scale model training pipelines
  • Experience shipping ML-powered products to millions of users or launching new ML product lines
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Publications or contributions to the ML research community

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$271,000/year to $347,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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