ZipRecruiter

Log In

1

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

Arete Associates

Scientist (Algorithm Developer)

Tucson, AZ · On-site

$85K - $145K/yr

Demonstrated experience with signal processing, image processing, computer vision, or machine learning * Experience programming in Python, C, C++, MATLAB or similar languages * Intellectual curiosity ...

Arete

Scientist (Algorithm Developer)

Tucson, AZ · On-site

Demonstrated experience with signal processing, image processing, computer vision, or machine learning * Experience programming in Python, C, C++, MATLAB or similar languages * Intellectual curiosity ...

Arete

Scientist (Algorithm Developer)

Tucson, AZ · On-site

Demonstrated experience with signal processing, image processing, computer vision, or machine learning * Experience programming in Python, C, C++, MATLAB or similar languages * Intellectual curiosity ...

Varsity Tutors

Data Science Tutor

Tucson, AZ · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

University of Arizona

Scientific Analyst II

Tucson, AZ · On-site

... machine learning, deep learning, and statistical modeling. * Strong data wrangling and preprocessing skills for large, heterogeneous datasets. * Expert-level programming skills in Python and/or R ...

Arete Associates

Scientist

Tucson, AZ · On-site

$80K - $130K/yr

Experience with machine learning, deep learning, artificial intelligence, object classification ... Parallel programming experience (threads, MPI, CUDA, etc.) * Active Secret Clearance The salary ...

Raytheon Technologies

Software Engineer II

Tucson, AZ · On-site

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Raytheon Technologies

Software Engineer II

Tucson, AZ · On-site

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Raytheon

Software Engineer II

Tucson, AZ

$92K - $126K/yr

Our engineers engage in the full software development life cycle within agile teams, focusing on areas like real-time systems, machine learning, cybersecurity, and DevOps. Join our team of creative ...

Varsity Tutors

Python Tutor

Tucson, AZ · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Top Engineer

X-Midas Software Engineer

Tucson, AZ

Continuous learning is built into the job as you tackle new DSP challenges and expand your skills ... The company values disciplined engineering, so you will have the autonomy to deliver high‑quality ...

Mesa Labs

Firmware Engineer

Tucson, AZ · On-site

$80K - $100K/yr

Implement solutions in machine language, assembly, and high-level languages (C, C++). * Testing ... Continuous Learning & Improvement: * Apply company policies, procedures, and engineering standards ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Tucson, AZ

Machine Learning Engineer information

See Tucson, AZ salary details

$29.3K

$119.6K

$179.7K

How much do machine learning engineer jobs pay per year?

As of Jul 21, 2026, the average yearly pay for machine learning engineer in Tucson, AZ is $119,569.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,200.00 and $143,900.00 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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Tucson, AZ? The most popular types of Machine Learning Engineer jobs in Tucson, AZ are:
What are popular job titles related to Machine Learning Engineer jobs in Tucson, AZ? For Machine Learning Engineer jobs in Tucson, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Tucson, AZ look for? The top searched job categories for Machine Learning Engineer jobs in Tucson, AZ are:
What cities near Tucson, AZ are hiring for Machine Learning Engineer jobs? Cities near Tucson, AZ with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Tucson, AZ as of July 2026, with employment types broken down into 84% Full Time, 8% Part Time, and 8% Contract. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $119,569 per year, or $57.5 per hour.
Scientific Analyst II

Scientific Analyst II

University of Arizona

Tucson, AZ

Other

Re-posted yesterday

University Of Arizona rating

7.2

Company rating: 7.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

345th of 555 rated colleges and universities

Job description

Data Analysis and Machine Learning Pipeline Development:

  • Under moderate guidance collaborate in the design, develop, and execution of machine learning and AI-driven analytical pipelines to analyze large-scale biomedical datasets from UK Biobank, All of Us, Insight, and electronic medical records.
  • Apply supervised and unsupervised machine learning algorithms (e.g., logistic regression, random forests, deep learning) to identify risk factors, biomarkers, and patterns associated with neurodegenerative diseases and the effects of menopausal hormone therapy (MHT) on brain health.
  • Collaborate on the development and validation of predictive models integrating genomic, clinical, lifestyle, and imaging data using general knowledge of principals, theories and concepts.

Drug Repurposing Research and Bioinformatics Analysis:

  • Collaborating in computational drug repurposing analyses to identify existing FDA-approved compounds with potential efficacy for AD, PD, MS, and ALS prevention and treatment. Integrate multi-omics data (genomics, transcriptomics, proteomics) with clinical outcomes data to prioritize drug candidates.
  • Collaborate with wet lab and clinical teams to support translational interpretation of findings.

Epidemiological and Clinical Data Management and Harmonization:

  • Access, curate, harmonize, and manage large population-based datasets including UK Biobank, All of Us, and institutional EMR data.
  • Ensure data quality, reproducibility, and compliance with data use agreements and IRB protocols.
  • Collaborate in the develop and maintenance of reproducible data pipelines using Python, R, and high performance computer.
  • Perform statistical analyses including survival analysis, longitudinal modeling, and causal inference.

Scientific Communication, Dissemination, and Collaboration:

  • Compare and contribute to peer-reviewed manuscripts, conference presentations, and grant applications reporting research findings on MHT, menopause, and neurodegenerative disease.
  • Present results to interdisciplinary research teams, departmental seminars, and external stakeholders.
  • Collaborate closely with Dr. Francesca Vitali, co-investigators, and consortium partners. Maintain thorough documentation of analytical methods to ensure transparency and reproducibility.
  • Participate in lab meetings, journal clubs, and professional development activities.

Research Infrastructure and Continuous Improvement:

  • Maintain and improve lab computational infrastructure, including code repositories (GitHub), analytical workflows, and documentation standards.
  • Evaluate and adopt emerging AI/ML tools and methodologies relevant to brain science research.
  • Assist in training junior lab members or graduate students on data science methods and tools as needed.
  • Stay current with literature in neurodegenerative disease, computational.

Knowledge, Skills and Abilities:

  • Strong theoretical and applied knowledge of machine learning, deep learning, and statistical modeling.
  • Strong data wrangling and preprocessing skills for large, heterogeneous datasets.
  • Expert-level programming skills in Python and/or R; proficiency with ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Knowledge of drug repurposing methodologies or network pharmacology.
  • Knowledge and familiarity with electronic medical records data analysis.
  • Knowledge and proficiency with SQL and database management.
  • Ability to collaborate effectively within interdisciplinary teams spanning data science, neuroscience, clinical research, and epidemiology.
  • Ability to manage multiple concurrent projects and meet deadlines.
  • Ability to critically evaluate scientific literature and translate findings into research hypotheses and analytical strategies.
  • Ability to communicate complex analytical results clearly to both technical and non-technical audiences.

What University Of Arizona employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply