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Machine Learning Engineer Jobs in Arizona (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Phoenix, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tempe, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Machine Learning Tutor

Glendale, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Machine Learning Tutor

Scottsdale, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Machine Learning Tutor

Chandler, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Gilbert, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tucson, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Mesa, AZ · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Arizona

Machine Learning Engineer information

See Arizona salary details

$29.4K

$120K

$180.3K

How much do machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for machine learning engineer in Arizona is $119,998.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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 Arizona? The most popular types of Machine Learning Engineer jobs in Arizona are:
What are popular job titles related to Machine Learning Engineer jobs in Arizona? For Machine Learning Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Arizona look for? The top searched job categories for Machine Learning Engineer jobs in Arizona are:
What cities in Arizona are hiring for Machine Learning Engineer jobs? Cities in Arizona with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in AZ? For Machine Learning Engineer jobs in AZ, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Python Unix machine learning Support Engineer

Python Unix machine learning Support Engineer

Centraprise

Chandler, AZ • On-site

Full-time

Posted 22 days ago

Job description

Job Title : Python Unix machine learning Support Engineer
Job Location : Chandler, AZ (ONSITE)
Job Type : Full-Time
Job Description:
Python Unix machine learning Support Engineer
Must Have Technical/Functional Skills
Unix, ShellScripting, Python, Machine learning, Production Support
Roles & Responsibilities
• System Configuration: Configuring Unix systems to meet specific requirements and standards.
• Troubleshooting: Identifying and resolving issues with Unix systems and applications.
• Scripting: Automating repetitive tasks using Python scripts.
• Performance Optimization: Analyzing and improving the performance of Unix systems.
• Documentation: Creating and maintaining system documentation and guides.
• Collaboration: Working with other teams and departments to ensure Unix systems are integrated and functional.
• Implement AI workflows using Python, agent frameworks, and orchestration tools
• Develop LLM pipelines including prompt engineering, prompt chaining, memory, tool calling, and multi-agent coordination
• Integrate LLMs with enterprise systems and APIs
• These roles are essential for maintaining the reliability and efficiency of Unix-based systems, and Python skills
can be leveraged to automate and streamline these tasks.
• Designed, developed, and deployed machine learning models using supervised and unsupervised learning
techniques to solve real world business problems.
• Worked with Python ML libraries including Scikit learn, TensorFlow, PyTorch, Pandas, NumPy, and Matplotlib.
• Deployed models using REST APIs, Docker, or cloud platforms (AWS / Azure / GCP) to support production
use cases.

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