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Mlops Engineer Jobs in Arizona (NOW HIRING)

AIML Engineer Job Location: Scottsdale - Arizona - USA Job Type: Contract to Hire ... Design and implement scalable MLOps supportive data pipelines for data ingestion processing and ...

Contribute to cloud-native ML pipelines and AI application deployment using MLOps, APIs, Docker, and Kubernetes * Collaborate cross-functionally with Security, Risk, Engineering, Governance, and Data ...

Senior AI/ML & IVR Engineer GCP

Scottsdale, AZ · On-site

$105K - $145K/yr

Implement robust MLOps for model monitoring, versioning, CI/CD, retraining, and performance ... Data engineering skills: ETL/ELT, real-time and batch pipelines * Excellent communication ...

Apply MLOps best practices for reproducibility, versioning, and governance of ML models. Required Qualifications: 5 years experience in DevOps, CloudOps, or ML Ops. 5 years experience with GCP AIML ...

AI/ML Engineer Location: Phoenix, AZ (Day 1 onsite - Hybrid 3 days a week in office) Duration ... Exposure to MLOps, workflow orchestration, and data-processing technologies, such as MLflow ...

MLOps & Production Engineering * Build and maintain MLOps infrastructure for model training, experiment tracking (MLflow, Weights & Biases), versioning, and deployment. * Containerize and deploy ML ...

MLOps & Production Engineering * Build and maintain MLOps infrastructure for model training, experiment tracking (MLflow, Weights & Biases), versioning, and deployment. * Containerize and deploy ML ...

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Lead Data & AI Engineer Location: Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay ... MLOps practices including versioning, CI/CD, monitoring, and drift detection. · Implement data ...

Data and AI Engineer II

Phoenix, AZ · On-site

$109K - $131K/yr

Utilize Snowflake, Azure, and DevOps/DataOps/MLOps practices to deliver enterprise-quality Python and SQL solutions and identify optimization opportunities. * Independently pursue training and ...

Data and AI Engineer II

Phoenix, AZ

$113K - $136K/yr

Utilize Snowflake, Azure, and DevOps/DataOps/MLOps practices to deliver enterprise-quality Python and SQL solutions and identify optimization opportunities. * Independently pursue training and ...

New

Data and AI Engineer II

Phoenix, AZ

$109K - $131K/yr

Utilize Snowflake, Azure, and DevOps/DataOps/MLOps practices to deliver enterprise-quality Python and SQL solutions and identify optimization opportunities. * Independently pursue training and ...

New

Data and AI Engineer II

Phoenix, AZ

$109K - $131K/yr

Utilize Snowflake, Azure, and DevOps/DataOps/MLOps practices to deliver enterprise-quality Python and SQL solutions and identify optimization opportunities. Independently pursue training and research ...

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Showing results 1-20

Mlops Engineer information

See Arizona salary details

$97.6K

$153.1K

$177.7K

How much do mlops engineer jobs pay per year?

As of Aug 31, 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.

Machine Learning Operations (MLOps) Engineer

Phoenix, AZ • On-site

Kforce Technology Staffing
IT Services • 1 - 5K employees

$101K - $134K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


Job description

RESPONSIBILITIES:
Kforce has a client that is seeking a Machine Learning Operations (MLOps) Engineer (Snowflake) in Phoenix, AZ.
Summary:
We are seeking a Senior MLOps Engineer to help design and build an enterprise-scale machine learning platform from the ground up. This is a unique opportunity to establish a modern MLOps ecosystem on Snowflake, supporting end-to-end model development, deployment, and lifecycle management.
The platform will be built on a medallion architecture (Bronze, Silver, Gold), enabling machine learning models to consume trusted, governed data products with full lineage, scalability, and performance. This role will play a key part in shaping standards, processes, and tooling as the platform evolves from MVP to enterprise scale.
Key Responsibilities:
* Architect and build a production-grade MLOps platform on Snowflake, leveraging Snowpark, Snowflake ML, Model Registry, and Feature Store
* Design and operationalize reusable pipelines for training, validation, deployment, inference, and monitoring
* Align ML workflows with Bronze, Silver, and Gold medallion layers to ensure consistent use of trusted data
* Establish model lifecycle management standards, including versioning, approvals, promotion gates, and rollback strategies
* Partner with data scientists to productionize models into scalable, reliable services
* Implement model observability for performance, drift, bias, and data quality, with alerting and SLOs
* Automate retraining and refresh processes using Snowflake Tasks, Dynamic Tables, and event-driven orchestration
* Collaborate with data engineering teams to ensure reliable and reusable feature pipelines
* Define and implement CI/CD pipelines for ML systems, including testing frameworks and release controls
* Drive governance across security, compliance, auditability, reproducibility, and responsible AI practices
* Lead platform maturation, including documentation, developer enablement, and operational runbooks
REQUIREMENTS:
* 5+ years of experience in ML Engineering, MLOps, or platform engineering
* Strong Python and SQL skills, with experience building production ML pipelines
* Hands-on experience with Snowflake data platforms (Snowpark and Snowflake ML strongly preferred)
* Experience with model deployment, versioning, monitoring, and lifecycle governance
* Experience implementing CI/CD and testing strategies for ML systems
* Strong understanding of feature engineering, training-serving consistency, and data quality controls
* Experience working with cloud platforms (AWS preferred)
* Proven ability to collaborate across data science, data engineering, and business teams
Preferred Qualifications:
* Experience with Snowflake Model Registry and Feature Store
* Background in medallion/lakehouse data architectures
* Experience with dbt or similar transformation tools
* Familiarity with streaming or near real-time ML inference
* Experience in high-volume operational environments (e.g., logistics, fleet, routing)
* Prior experience building greenfield platforms and establishing standards from scratch
This role can be performed fully remotely but there is a preference for Phoenix local talent. This role has the potential to convert to FTE with Kforce's client.
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.

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About Kforce

Sourced by ZipRecruiter

Kforce is a professional staffing services firm that is located in Tampa, Florida, US. Operational since 1962, it specializes in flexible and direct hire staffing in Technology and Finance & Accounting, engaging over 23,000 highly skilled professionals annually with more than 4,000 customers. Kforce operates within various industry sectors such as healthcare, financial services, communications, and government. Their mission is to have a meaningful impact on all the lives they serve, with a focus on integrity, respect, and trust.

Industry

It services and finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Tampa, FL, US