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Machine Learning Jobs in Tempe, AZ (NOW HIRING)

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

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Machine Learning information

See Tempe, AZ salary details

$24.4K

$40.8K

$84.3K

How much do machine learning jobs pay per year?

As of Jun 10, 2026, the average yearly pay for machine learning in Tempe, AZ is $40,785.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,100.00 and $44,100.00 per year, depending on experience, location, and employer.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What are the key skills and qualifications needed to thrive in the Machine Learning position, and why are they important?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are the most commonly searched types of Machine Learning jobs in Tempe, AZ? The most popular types of Machine Learning jobs in Tempe, AZ are:
What are popular job titles related to Machine Learning jobs in Tempe, AZ? For Machine Learning jobs in Tempe, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning jobs in Tempe, AZ look for? The top searched job categories for Machine Learning jobs in Tempe, AZ are:
What cities near Tempe, AZ are hiring for Machine Learning jobs? Cities near Tempe, AZ with the most Machine Learning job openings:
Senior Machine Learning Engineer

$110K - $180K/yr

Other

Posted 25 days ago


Job description

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.