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Machine Learning Software Engineer Jobs in Phoenix, AZ

Machine Learning Engineer

Phoenix, AZ

$55.25 - $73.25/hr

Machine Learning Engineer Location: Phoenix, AZ (Onsite) Required Skills Machine Learning, Python ... and software architecture Advanced Python programming experience; Java knowledge is a plus ...

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As an Applied Machine Learning Engineer, you will support informed decision-making around the ... The position is onsite in Chandler, AZ and works closely with software, infrastructure, simulation ...

As a software developer, you will utilize modern methodologies and technologies to innovate and ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

Job Position: - Senior Software Engineer Job Location: - Phoenix AZ (100% onsite) Job Type ... Conceptual understanding of machine learning fundamentals and model telemetry. Additional Skills

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Machine Learning Software Engineer information

See Phoenix, AZ salary details

$63K

$146.5K

$204K

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

As of May 30, 2026, the average yearly pay for machine learning software engineer in Phoenix, AZ is $146,478.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $171,800.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

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

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.
What are popular job titles related to Machine Learning Software Engineer jobs in Phoenix, AZ? For Machine Learning Software Engineer jobs in Phoenix, AZ, the most frequently searched job titles are:
Senior Machine Learning Engineer

$110K - $180K/yr

Other

Posted 14 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.