1

Machine Learning Engineer Python Jobs in Arizona

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research ... Proficient in Python * Proficient in LLM architectures, optimization and model training dynamics.

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 ...

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 ...

next page

Showing results 1-20

Machine Learning Engineer Python information

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.
What cities in Arizona are hiring for Machine Learning Engineer Python jobs? Cities in Arizona with the most Machine Learning Engineer Python job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Prime Solutions Group, Inc.

Goodyear, AZ โ€ข On-site

$110K/yr

Full-time

Posted 11 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.