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Artificial Intelligence Machine Learning Engineer Jobs in Phoenix, AZ

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

AI & Machine Learning Engineer

Chandler, AZ ยท On-site

$100K - $110K/yr

Write advanced SQL queries to transform healthcare data into actionable intelligence * Collaborate ... Knowledge of Machine Learning and Generative AI frameworks * Strong engineering fundamentals and ...

Lead AI and Data Science Engineer II

Tempe, AZ ยท On-site

$98K - $129K/yr

... machine learning, and application development to solve high-priority people challenges. You will ... Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that ...

Showing results 21-40

Artificial Intelligence Machine Learning Engineer information

See Phoenix, AZ salary details

$31.3K

$127.9K

$192.1K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for artificial intelligence machine learning engineer in Phoenix, AZ is $127,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

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

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

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

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Phoenix, AZ?

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

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Phoenix, AZ look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Phoenix, AZ are:

What cities near Phoenix, AZ are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Phoenix, AZ with the most Artificial Intelligence Machine Learning Engineer job openings:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Phoenix, AZ as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $127,856 per year, or $61.5 per hour.

Machine Learning Engineer with Security Clearance

Prime Solutions Group, Inc

Goodyear, AZ โ€ข On-site

$110K/yr

Other

Re-posted yesterday


Job description

Turn machine learning into real-world mission capability.
PSG is seeking a Machine Learning Engineer to design, build, and deploy AI/ML solutions that power mission-critical systems. This role focuses on taking models from concept to productionโ€”developing pipelines, integrating models into software systems, and ensuring performance, scalability, and reliability in real-world environments. Youโ€™ll work at the intersection of machine learning, software engineering, and DevSecOps, collaborating with cross-functional teams to deliver secure, production-ready AI solutions supporting national security missions. What Youโ€™ll Do
- Design, build, and maintain ML pipelines for data preparation, training, evaluation, and deployment - Develop and optimize ML models and applications using Python and frameworks like PyTorch or TensorFlow - Integrate models into production systems (APIs, batch pipelines, real-time services) - Implement model validation, evaluation metrics, and performance monitoring - Improve model accuracy, scalability, and efficiency through tuning and data strategy improvements - Collaborate with data engineers and domain experts to prepare and validate datasets - Partner with DevSecOps/MLOps teams to deploy ML solutions in secure environments - Troubleshoot model and pipeline issues; perform root cause analysis and optimization - Contribute to technical documentation, test plans, and operational runbooks - Participate in design reviews, architecture discussions, and Agile development processes - Mentor junior engineers and promote engineering best practices Requirements
- U.S. Citizenship - Active Top Secret Clearance (SCI eligibility; CI Poly preferred or ability to obtain) - Bachelorโ€™s degree in Computer Science, Engineering, Data Science, or related field - 4+ years of experience in: - Machine Learning Engineering - Applied AI/ML development - Production ML systems - Strong Python skills and experience with ML libraries (NumPy, pandas, scikit-learn, PyTorch, TensorFlow) - Experience developing, training, and deploying ML models in real-world applications - Solid understanding of the ML lifecycle (data > training > validation > deployment > monitoring) - Experience building maintainable, production-quality software - Familiarity with Docker and cloud environments (AWS, Azure, or GCP) - Experience working in Agile and CI/CD environments - Strong problem-solving, communication, and collaboration skills Preferred Qualifications
- Masterโ€™s degree in a related field - Experience with computer vision, image/video analytics, or sensor data (e.g., RF, SAR) - Experience transitioning models from research to production environments - Familiarity with experiment tracking, model versioning, and reproducibility practices - Experience with GPU-based ML workflows and cloud ML platforms - Background in defense, intelligence, or other regulated environments Why Join PSG?
At PSG, youโ€™re not just taking a jobโ€”youโ€™re building technology that matters.
- Competitive compensation & benefits - 9/80 flexible work schedule - Professional development & tuition assistance - Small, agile team with high ownership and visibility - Work on mission-critical systems supporting national security - Opportunities to grow across AI/ML, software engineering, and platform development Bring your machine learning expertise to PSG and help deliver the next generation of secure, intelligent, mission-driven systems. Salary Description
Salary range starts at $110,000 with the potential for higher compensation based on experience, skills, and mission needs.