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Mlops Engineer Jobs in Arizona (NOW HIRING)

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... MLOps pipelines. Communication and Influence Clearly articulate technical risks, trade-offs, and ...

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... MLOps pipelines. Communication and Influence Clearly articulate technical risks, trade-offs, and ...

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handson experience in ... Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift ...

We are seeking for Staff AI Solutions Engineer to help deliver scalable AI/ML solutions across ... Strong knowledge of cloud platforms (Azure preferred), MLOps, and data governance. * Excellent ...

Senior Data & AI Engineer

Phoenix, AZ · On-site

$100K - $136K/yr

Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift ... Machine learning: feature engineering, model training/evaluation, and deployment (e.g ...

We are seeking for Staff AI Solutions Engineer to help deliver scalable AI/ML solutions across ... Strong knowledge of cloud platforms (Azure preferred), MLOps, and data governance. * Excellent ...

Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

The Opportunity As part of the Data and Analytics Engineering team, you will serve as both a ... with MLOps tooling and CI/CD pipelines for ML - Experience with vector databases and semantic ...

... MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability * Partner with software engineers, data engineers ...

Senior Software Engineer

Tempe, AZ · On-site

$91K - $163K/yr

Mentor development teams, fostering best practices in software engineering and agile delivery ... MLOps practices (CI/CD, monitoring, model versioning) * 6 months of experience designing and ...

Senior Software Engineer

Tempe, AZ · Remote

$91K - $163K/yr

Mentor development teams, fostering best practices in software engineering and agile delivery ... MLOps practices (CI/CD, monitoring, model versioning) * 6 months of experience designing and ...

... MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability * Partner with software engineers, data engineers ...

Showing results 41-60

Mlops Engineer information

See Arizona salary details

$97.6K

$153.1K

$177.7K

How much do mlops engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for mlops engineer in Arizona is $153,133.00, according to ZipRecruiter salary data. Most workers in this role earn between $147,088.00 and $165,049.00 per year, depending on experience, location, and employer.

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive as an MLOps engineer, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

What are the most commonly searched types of Mlops Engineer jobs in Arizona?

The most popular types of Mlops Engineer jobs in Arizona are:

What are popular job titles related to Mlops Engineer jobs in Arizona?

For Mlops Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer jobs in Arizona look for?

The top searched job categories for Mlops Engineer jobs in Arizona are:

What cities in Arizona are hiring for Mlops Engineer jobs?

Cities in Arizona with the most Mlops Engineer job openings:

Infographic showing various Mlops Engineer job openings in Arizona as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $153,133 per year, or $73.6 per hour.

AI Security Engineer Manager

Deloitte

Tempe, AZ • On-site

Full-time

Re-posted 25 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services


Job description

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 8/29/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The successful candidate would possess these skills

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

  • Cyber Security
  • Technology Support
  • Technology & Infrastructure
  • Applications
  • Relationship Management
  • Strategy & Communications
  • Project Management
  • Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

  • Risk & Compliance
  • Identity & Access Management
  • Data Protection
  • Cyber Design
  • Incident Response
  • Security Architecture
  • Business Partnership

Qualifications

Required:

  • Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
  • Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
  • Minimum 1 year of people and/or process management experience

Preferred:

  • Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
  • Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
  • Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
  • Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
  • Knowledge of data protection, identity/access management, and secure architecture patterns
  • Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
  • Strong communication skills with the ability to translate technical concepts into business-relevant insights

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118,700 to $243,700.  

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. 

EA_ExpHire
RITM10427821

Qualifications:

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 8/29/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The successful candidate would possess these skills

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

  • Cyber Security
  • Technology Support
  • Technology & Infrastructure
  • Applications
  • Relationship Management
  • Strategy & Communications
  • Project Management
  • Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

  • Risk & Compliance
  • Identity & Access Management
  • Data Protection
  • Cyber Design
  • Incident Response
  • Security Architecture
  • Business Partnership

Qualifications

Required:

  • Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
  • Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
  • Minimum 1 year of people and/or process management experience

Preferred:

  • Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
  • Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
  • Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
  • Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
  • Knowledge of data protection, identity/access management, and secure architecture patterns
  • Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
  • Strong communication skills with the ability to translate technical concepts into business-relevant insights

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A...


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