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Physics Informed Machine Learning Jobs in Phoenix, AZ

Infinia Search Inc

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Applied Machine Learning Engineer

Chandler, AZ · On-site

$60 - $95/hr

As an Applied Machine Learning Engineer, you will support informed decision-making around the application of machine learning and AI models in safety- and reliability-constrained systems. This role ...

Deloitte

Data Science Consultant

Tempe, AZ · On-site

Required : • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. • At least 2+ years of industry ...

Deloitte

Data Science Consultant

Tempe, AZ

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. * At least 2+ years of industry experience outside ...

USAA

AI/ML Engineer II

Phoenix, AZ · On-site

$116.10K - $139.40K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine ... Physics, or related field followed by 2 years of work experience in job offered or in a related ...

USAA

AI/ML Engineer II

Phoenix, AZ · On-site +1

$113.70K - $136.50K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine ... Physics, or related field followed by 2 years of work experience in job offered or in a related ...

TEEMA

Principal Software Engineer / Architect

Phoenix, AZ · Remote

$165K - $190K/yr

... Physics, or equivalent experience Preferred * Large-scale Laravel/Django experience * Node.js, concurrency, asynchronous processing * Leadership in team management or architecture * Machine learning ...

TSMC

Quality Management Engineer

Phoenix, AZ

$88.60K - $114.50K/yr

Predictive analytics and statistical applications including modeling, machine learning, data ... B.S. or higher in Mathematics, Statistical, Electrical Engineering, Materials Science, Physics ...

TSMC

Quality Management Engineer

Phoenix, AZ · On-site

$88.60K - $114.50K/yr

Predictive analytics and statistical applications including modeling, machine learning, data ... B.S. or higher in Mathematics, Statistical, Electrical Engineering, Materials Science, Physics ...

Stride, Inc.

AI Architect

Phoenix, AZ · On-site

Drives the conception, prototyping, and deployment of machine learning models-particularly in ... Bachelor's degree in Computer Science, Math, Physics, Engineering, or related quantitative field ...

INTEL

Packaging Module Development Engineer

Phoenix, AZ

$127.40K - $179.90K/yr

... Physics/Applied Physics, or a related field with 3+ years of experience or PhD in Mechanical ... intelligence and machine learning concepts. Preferred Qualifications: One or more years of ...

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

As of May 28, 2026, the average hourly pay for physics informed machine learning in Phoenix, AZ is $19.92, according to ZipRecruiter salary data. Most workers in this role earn between $12.40 and $25.29 per hour, depending on experience, location, and employer.

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 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.
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Physics Informed Machine Learning jobs near you
Applied Machine Learning Engineer

Applied Machine Learning Engineer

Infinia Search Inc

Chandler, AZ • On-site

$60 - $95/hr

Contractor

Medical, Dental, Vision

Posted 7 days ago

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Job description

Must be a U.S. Citizen
Secret Clearance preferred
This position will to support mission-critical aerospace and defense programs. As an Applied Machine Learning Engineer, you will support informed decision-making around the application of machine learning and AI models in safety- and reliability-constrained systems. This role focuses on evaluating tradeoffs between retrieval-based approaches, fine-tuning, targeted training, and non-ML solutions. The position is onsite in Chandler, AZ and works closely with software, infrastructure, simulation, and GNC engineering teams.

Requirements

· Bachelor’s degree in Computer Science, Engineering, Mathematics, or related STEM field

· 3+ years of applied machine learning experience with production systems

· Demonstrated experience making technical tradeoff decisions around:

· RAG vs fine-tuning vs lightweight adaptation

· Model scope, training data selection, and evaluation

· Strong understanding of model failure modes, overfitting, and distribution shift

· Experience deploying ML in environments where correctness and reliability matter

· Ability to clearly communicate ML risks and limitations to non-ML engineers

· U.S. Citizenship

· Preferred Qualifications

· Experience with simulation, autonomous systems, aerospace, or defense programs

· Exposure to guidance, navigation, or control systems

· Experience working with hybrid ML + classical systems

· Familiarity with regulated or compliance-driven software environments

· Active or prior DoD security clearance

Responsibilities

· Evaluate when machine learning should or should not be applied to engineering problems

· Advise teams on tradeoffs between RAG, fine-tuning, and targeted model training

· Support definition of heuristics for model selection, evaluation, and retraining

· Identify and mitigate ML failure modes in system and simulation contexts

· Collaborate with GNC, software, and infrastructure teams on safe ML integration

Company Description

We’re Infinia Search. We’re a relationship-driven search firm that proves that talent, ambition, curiosity, and an infinite work ethic creates exponential results for our clients and candidates.
Infinia Search logo

About Infinia Search

Sourced by ZipRecruiter

Whether we are recruiting top talent or building out a managed team, Infinia’s focus is developing and strengthening relationships with both clients and candidates, because placing professionals is about more than running web searches and filling empty seats. It’s about the human connection.

Industry

Recruiting and staffing services

Company size

201 - 500 Employees

Headquarters location

Kennett Square, PA, US

Year founded

2016

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