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Machine Learning Secret Clearance Jobs in Arizona

Minimum Secret clearance is required * Compliance with DoD 8140 / 8570 IAT Level II certification ... Beats, Machine Learning, and REST API integration * Demonstrated ability to utilize Ansible ...

USIEM Elastic Engineer

Sierra Vista, AZ · On-site

$110K - $150K/yr

Minimum Secret Clearance is required * Compliance with DoD 8140 / 8570 IAT Level II certification ... Beats, Machine Learning, and REST API integration * Demonstrated ability to utilize Ansible ...

Provide necessary shop floor assistance to the Production Machine Operators in maintaining machine ... Must be able to obtain and maintain a Secret Clearance Required Education : * High School Diploma ...

Provide necessary shop floor assistance to the Production Machine Operators in maintaining machine ... Must be able to obtain and maintain a Secret Clearance Required Education : * High School Diploma ...

Showing results 21-40

Machine Learning Secret Clearance information

What are the key skills and qualifications needed to thrive as a machine learning secret clearance?

To thrive as a Machine Learning Engineer with Secret Clearance, you need a solid background in computer science, mathematics, and machine learning theory, typically supported by a relevant degree and eligibility for security clearance. Familiarity with frameworks like TensorFlow or PyTorch, programming languages such as Python, and secure data handling protocols is essential, and certifications like CompTIA Security+ can be valuable. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with interdisciplinary teams in sensitive environments. These skills ensure the development of robust, secure, and innovative AI solutions that meet strict government or defense requirements.

What is the difference between Machine Learning Secret Clearance vs Data Scientist with Secret Clearance?

AspectMachine Learning Secret ClearanceData Scientist with Secret Clearance
Required CredentialsSecurity clearance, specialized machine learning knowledge, programming skillsSecurity clearance, statistical, programming, and data analysis skills
Work EnvironmentGovernment agencies, defense contractors, classified projectsGovernment agencies, private sector, research institutions
Employer & Industry UsagePrimarily defense, intelligence, aerospaceWide range including government, tech, finance
Common Search & ComparisonYesYes

Both roles require security clearance and technical expertise, but Machine Learning Secret Clearance focuses more on developing AI models for classified projects, while Data Scientist with Secret Clearance emphasizes data analysis and insights across various sectors. The roles often overlap in government and defense sectors, but differ in specific skill sets and project focus.

What unique challenges might I face working as a machine learning secret clearance, and how does this affect daily responsibilities?

Working as a Machine Learning Engineer with Secret Clearance often involves handling sensitive or classified data, which introduces unique challenges such as adhering to strict security protocols and limited access to certain resources or external tools. Your daily responsibilities may include developing models in secure environments, collaborating closely with cross-functional teams cleared at similar levels, and ensuring all work complies with government regulations. While the work can be highly impactful and intellectually stimulating, it requires strong attention to detail, adaptability, and an understanding of data security practices.

What is a machine learning secret clearance?

A Machine Learning Secret Clearance job involves developing and implementing machine learning models and algorithms within organizations that require employees to hold a U.S. government Secret security clearance. These roles typically support classified projects for government agencies or defense contractors, ensuring that sensitive data and methods are handled securely. Professionals in these positions combine expertise in artificial intelligence with knowledge of security protocols, working on tasks like data analysis, predictive modeling, and automation within a secure environment. The Secret clearance requirement demonstrates an individual's trustworthiness and eligibility to access classified information, which is essential for national security work.
What are popular job titles related to Machine Learning Secret Clearance jobs in Arizona? For Machine Learning Secret Clearance jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Machine Learning Secret Clearance jobs? Cities in Arizona with the most Machine Learning Secret Clearance job openings:
Infographic showing various Machine Learning Secret Clearance job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Principal Data Scientist - Factory Intelligence (Tucson)

RTX

Tucson, AZ • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


RTX rating

8.2

Company rating: 8.2 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

38th of 72 rated aerospace companies


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

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.

  • 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
  • holidays
  • 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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