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Ai Machine Learning Engineer Jobs in Arizona (NOW HIRING)

Black Rock Group

Machine Learning Engineer

Phoenix, AZ

$55.25 - $73.25/hr

Machine Learning Engineer Location: Phoenix, AZ (Onsite) Required Skills Machine Learning, Python ... AI/ML governance in regulated industries is a plus Preferred Experience NLP model development ...

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 ...

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Implement CICD pipelines for ML and AI-driven applications. Monitor, troubleshoot, and optimize ... Google Cloud Professional Machine Learning Engineer Google Cloud Professional Data Engineer AWS ...

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Ai Machine Learning Engineer information

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$29.4K

$120K

$180.3K

How much do ai machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for ai 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.

What are the key skills and qualifications needed to thrive as an AI Machine Learning Engineer, and why are they important?

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI Machine Learning Engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

What is an AI Machine Learning Engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

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

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

What are popular job titles related to Ai Machine Learning Engineer jobs in Arizona? For Ai Machine Learning Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Ai Machine Learning Engineer jobs in Arizona look for? The top searched job categories for Ai Machine Learning Engineer jobs in Arizona are:
Ai Machine Learning Engineer jobs near you
Infographic showing various Ai Machine Learning Engineer job openings in Arizona as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $119,998 per year, or $57.7 per hour.

Machine Learning Engineer

Black Rock Group

Phoenix, AZ

$55.25 - $73.25/hr

Other

Posted 7 days ago

Job description

Machine Learning Engineer

Location: Phoenix, AZ (Onsite)

Required Skills

Machine Learning, Python, SQL, APIs, NLP, NoSQL, Spark / PySpark, CI/CD

Job Description

We are looking for a strong Machine Learning Engineer with hands-on experience in developing, deploying, and optimizing ML models in enterprise environments. The ideal candidate should have expertise in Classical Machine Learning, NLP, Python development, and scalable data processing systems.

Required Qualifications

Bachelor s or higher degree in Data Science, Computer Science, Engineering, Information Systems, or related field

Hands-on experience building and deploying Machine Learning models including Classical ML and NLP solutions

Strong understanding of ML algorithms, frameworks, libraries, and software architecture

Advanced Python programming experience; Java knowledge is a plus

Experience integrating ML models into existing applications in both batch and real-time environments

Strong SQL skills with experience writing complex queries and optimizing data pipelines

Experience with NoSQL databases is a plus

Familiarity with Big Data technologies such as Spark, PySpark, Hive, MapReduce

Working knowledge of UNIX/Linux commands

Experience using GitHub and CI/CD pipelines

Strong analytical, problem-solving, and communication skills

Experience with AI/ML governance in regulated industries is a plus

Preferred Experience

NLP model development

Enterprise-scale ML deployments

Real-time inference/API integrations

Financial services or highly regulated industry background

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