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Machine Learning Engineer Jobs in Gilbert, AZ (NOW HIRING)

Pwc

AI Solutions Engineering Delivery Lead

Phoenix, AZ · On-site

$101K - $134K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Staffingine LLC

AI ML Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Programming Languages Python Pandas NumPy Scikitlearn SQL ... Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting

Intel

Senior AI / Data Science Engineer

Phoenix, AZ

$105K - $143K/yr

Lead development of advanced AI, Machine Learning, and Generative AI solutions that address ... Collaborate closely with Yield Engineering, Process Integration, Manufacturing, and Technology ...

IntraEdge

Senior AI/ML & IVR Engineer GCP

Scottsdale, AZ

$105K - $145K/yr

Design, build, and deploy machine learning pipelines and end-to-end AI solutions using GCP services ... Data engineering skills: ETL/ELT, real-time and batch pipelines * Excellent communication ...

Deloitte

Senior Forward Deployed Engineer- AWS

Tempe, AZ

$100K - $137K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Pwc

CTIO AI Engineering Manager

Phoenix, AZ · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Deloitte

Lead Forward Deployed Engineer - AWS

Tempe, AZ

$98K - $129K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning models into production environments. * Evaluate data quality, model performance ...

CNH Industrial N.V.

AI Development Engineer

Tempe, AZ · On-site

$111K - $163K/yr

Engineering and Technical Job Type for Job Posting: Full Time Working Mode for Job Posting: Hybrid ... Generating software systems derived from various Machine Learning (ML) techniques to drive ...

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Lead Data & AI Engineer Location: Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay ... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ...

Axosoft, LLC

Applied Data Scientist

Scottsdale, AZ · On-site

We're looking for a pragmatic, startup-minded Senior Machine Learning Engineer or Applied Data Scientist who can take an idea from concept to production. Sometimes that idea will come from the data.

Axosoft, LLC

Applied Data Scientist

Scottsdale, AZ · On-site

We're looking for a pragmatic, startup-minded Senior Machine Learning Engineer or Applied Data Scientist who can take an idea from concept to production. Sometimes that idea will come from the data.

GitKraken

Applied Data Scientist

Scottsdale, AZ · Remote

We're looking for a pragmatic, startup-minded Senior Machine Learning Engineer or Applied Data Scientist who can take an idea from concept to production. Sometimes that idea will come from the data.

Deloitte

Forward Deployed Engineer- AWS

Tempe, AZ

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Gilbert, AZ

Machine Learning Engineer information

See Gilbert, AZ salary details

$31.4K

$128.4K

$192.9K

How much do machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning engineer in Gilbert, AZ is $128,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $154,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Gilbert, AZ?

The most popular types of Machine Learning Engineer jobs in Gilbert, AZ are:

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For Machine Learning Engineer jobs in Gilbert, AZ, the most frequently searched job titles are:

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The top searched job categories for Machine Learning Engineer jobs in Gilbert, AZ are:

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Cities near Gilbert, AZ with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Gilbert, AZ as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,390 per year, or $61.7 per hour.

Advanced AI Engineer - Mechanical Engineering

Honeywell International, Inc.

Tempe, AZ • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

67th of 544 rated manufacturers

Job description


As an Advanced AI Engineer at Honeywell Aerospace, you will provide technical contributions to the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including wheels and brakes, fuel systems, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.
In this role, you will develop advanced AI surrogates and Physics-AI models, and contribute to the transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and contribute to the execution from concept through integration. Your work will impact engineering efficiency, product performance, and Honeywell's leadership in AI-enabled engineering design.
Key Responsibilities
  • Contribute to the creation of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
  • Create scripted FEA or CFD models to generate training data over parameter and load condition spaces.
  • Suggest ideas to drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
  • Research and test new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
  • Suggest improvements to current processes for efficient data generation, data handling, and model utilization.
  • Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model-based AI frameworks.
  • Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
  • Contribute to technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
  • Assist with outreach to traditional design and analysis engineering functions.

Qualifications
YOU MUST HAVE
  • Bachelor's degree from an accredited institution in technical disciplines such as the sciences, technology, engineering or mathematics.
  • 2 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling. Experience in a graduate program may be included.
  • 3 years with simulation scripting (Abaqus Python scripting interface, Ansys PyAnsys or APDL or similar open-source tools).
  • 5 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis
  • Experience mentoring others in specialty areas.
  • Experience with NVIDIA's physics-accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning

WE VALUE
  • Bachelor's or Master's degree in aerospace engineering, mechanical engineering, or a related engineering discipline.
  • Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
  • Experience with JAX for differentiable models
  • Experience working in structured machine learning deployment environments i.e. MLOps workflows
  • Experience with CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
  • Experience with AI model architectures used for surrogate modeling, such as but not limited to MeshGraphNets, Neural Operators, Physics-Informed and Physics-Attention models.
  • Experience with model visualization through tools such as PyVista, Matplotlib, Plotly, and others.
  • Awareness of considerations for deploying AI models into engineering design workflows or digital engineering ecosystems.
  • Awareness of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.

ABOUT HONEYWELL AEROSPACE
Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach, that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
BENEFITS OF WORKING FOR HONEYWELL AEROSPACE
Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:
  • Employer-subsidized medical, dental, vision and life insurance
  • Short-term and long-term disability coverage
  • 401(k) match, flexible spending accounts and health savings accounts
  • Employee assistance program and educational assistance
  • Parental leave and 12 paid holidays
  • Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: August 6, 2026
Sponsorship
We are currently not sponsoring applicants for work visas for this position. Applicants must be currently authorized to work in the United States on a full-time basis.
#LI-Hybrid
U.S. PERSON REQUIREMENTS
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status.

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906

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