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

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 ...

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 ...

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 ...

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

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AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

Knowledge of Machine Learning and Generative AI frameworks * Strong engineering fundamentals and problem-solving skills * A builder mindset -- curious, resourceful, fast-moving, and focused on ...

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Machine Learning Engineer information

See Chandler, AZ salary details

$30.9K

$126.5K

$190K

How much do machine learning engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for machine learning engineer in Chandler, AZ is $126,456.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,700.00 and $152,200.00 per year, depending on experience, location, and employer.

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-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants 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 AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Chandler, AZ? The most popular types of Machine Learning Engineer jobs in Chandler, AZ are:
What are popular job titles related to Machine Learning Engineer jobs in Chandler, AZ? For Machine Learning Engineer jobs in Chandler, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Chandler, AZ look for? The top searched job categories for Machine Learning Engineer jobs in Chandler, AZ are:
What cities near Chandler, AZ are hiring for Machine Learning Engineer jobs? Cities near Chandler, AZ with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Chandler, AZ as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $126,456 per year, or $60.8 per hour.

Senior Machine Learning Engineer

Prime Solutions Group, Inc.

Goodyear, AZ • On-site

$110K/yr

Full-time

Re-posted 18 days ago


Job description

Job Type
Full-time
Description
Prime Solutions Group (PSG), Inc. is an innovative digital engineering company founded in 2007 and headquartered in Goodyear, AZ. We specialize in advanced sensing, AI/ML, and digital engineering solutions, partnering with many of the nation's leading defense companies to deliver mission-critical technology.
Our work spans the full system lifecycle-from R&D to operational deployment-supporting the Department of Defense, Intelligence Community, and federal partners. At PSG, you'll join a small, agile team where your contributions have a direct impact while working alongside top-tier engineering talent.
Position Overview
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 production-developing pipelines, integrating models into software systems, and ensuring performance, scalability, and reliability in real-world environments.
You'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 You'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)
  • Bachelor'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
  • Master'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, you're not just taking a job-you'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.