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Machine Learning Biomedical Engineer Jobs in Tucson, AZ

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

QA Engineer - AI Trainer

Tucson, AZ · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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

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Machine Learning Biomedical Engineer information

See Tucson, AZ salary details

$29.8K

$121.7K

$182.9K

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

As of Jul 14, 2026, the average yearly pay for machine learning biomedical engineer in Tucson, AZ is $121,748.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,000.00 and $146,500.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What does a Machine Learning Biomedical Engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

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

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a Machine Learning Biomedical Engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.
What are popular job titles related to Machine Learning Biomedical Engineer jobs in Tucson, AZ? For Machine Learning Biomedical Engineer jobs in Tucson, AZ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biomedical Engineer jobs in Tucson, AZ look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Tucson, AZ are:
What cities near Tucson, AZ are hiring for Machine Learning Biomedical Engineer jobs? Cities near Tucson, AZ with the most Machine Learning Biomedical Engineer job openings:
Infographic showing various Machine Learning Biomedical Engineer job openings in Tucson, AZ as of July 2026, with employment types broken down into 2% Internship, 1% As Needed, 80% Full Time, 16% Part Time, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $121,748 per year, or $58.5 per hour.
Principal Data Scientist - Factory Intelligence

Principal Data Scientist - Factory Intelligence

Raytheon

Tucson, AZ

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

New


Raytheon rating

9.1

Company rating: 9.1 out of 10

Based on 95 frontline employees who took The Breakroom Quiz

3rd of 527 rated manufacturers


Job description

Date Posted:

2026-07-09

Country:

United States of America

Location:

US-AZ-TUCSON-M09 ~ 3350 E Hemisphere Loop ~ BLDG M09

Position Role Type:

Hybrid

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

Active and transferable U.S. government issued security clearance is required prior to start date.​ U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance​

Security Clearance Type:

DoD Clearance: Secret

Security Clearance Status:

Ability to obtain INTERIM U.S. government issued security clearance is required prior to start date

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. 

Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today’s mission and stay ahead of tomorrow’s threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense.


As a Principal Data Scientist – Factory Intelligence, you will play a key role in transforming factory data into actionable intelligence that directly impacts production performance. Working across Engineering, Operations, and Quality, you will lead the development and deployment of predictive analytics solutions that improve yield, reduce variation, and drive smarter decision-making at scale.

This is a hybrid role based in Tucson, Arizona.

What You Will Do:

  • Transform factory data into actionable intelligence that improves production performance.
  • Collaborate with Engineering, Operations, and Quality teams to build and deploy predictive analytics solutions.
  • Develop models that directly impact yield, reduce variation, and support smarter decision-making.
  • Design, deploy, and maintain production-grade machine learning solutions.
  • Build intuitive data visualization tools and statistical analysis applications.
  • Partner with stakeholders to translate complex data into clear, practical insights.
  • Provide technical leadership and mentor junior data scientists and engineers.
  • Establish best practices in applied data science across the organization.
  • Become a subject matter expert in factory test data and uncover opportunities for improvement.
  • Solve challenging, data-driven manufacturing problems and deliver measurable production enhancements.
  • Work directly with customers to ensure data is fully leveraged to improve performance.
  • Contribute to scalable, production-ready data science solutions and help advance the organization’s analytics standards.
  • Operate effectively in a fast-paced, multi-tasking environment.

Qualifications You Must Have:

  • Typically requires a University Degree or equivalent experience and a minimum of 8 years of prior relevant experience, or an Advanced Degree in a related field and a minimum of 5 years of experience
  • Experience developing in Python (NumPy, SciPy, scikit-learn, scikit-image) for production-grade statistical or machine learning applications (beyond academic examples)
  • Demonstrated experience deploying, maintaining, and scaling machine learning models in production environments
  • Experience with relational database management and SQL development
  • U.S. Citizen - Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance

Qualifications We Prefer:

  • Experience with statistical tools such as Minitab, R, JMP, or SAS
  • Strong knowledge of machine learning pipelines and MLOps practices (e.g., MLflow), including versioning, monitoring, and lifecycle management
  • Strong experience applying quantitative techniques (normalization, standardization, applied statistics) to analyze large, complex datasets and build deployable machine learning models, including in cloud environments such as AWS or Azure
  • Experience designing, training, fine-tuning, and deploying deep learning models using frameworks such as PyTorch or TensorFlow
  • Experience working with large language models (LLMs), including fine-tuning, evaluation, and deployment; or demonstrated deep knowledge of LLM concepts and architectures
  • Experience operating in a technical leadership or mentoring

Learn More & Apply Now

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.

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