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Ml Platform Engineer Jobs in Arizona (NOW HIRING)

Cable One, Inc.

Senior AI/ML Engineer

Phoenix, AZ · On-site +1

$98K - $135K/yr

The Senior AI/ML Engineer will serve as the technical authority for AI/ML platforms, agent architecture, Model Context Protocol (MCP) strategy, context engineering, orchestration, governance, and AI ...

Deloitte

AI Engineer Consultant

Tempe, AZ · Hybrid

... science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI ... solutions. This role is hands-on and delivery-oriented: you will ship production pipelines and ...

Virtuous

Lead Data Platform Engineer

Phoenix, AZ · On-site

$101K - $134K/yr

They are seeking a Lead Data Platform Engineer to design and build a robust data ecosystem that ... Preferred : • dbt certification strongly preferred • Experience enabling AI/ML or natural ...

Virtuous

Lead Data Platform Engineer

Phoenix, AZ · On-site

$101K - $134K/yr

They are seeking a Lead Data Platform Engineer to design, build, and own the systems that power ... Preferred : • dbt certification strongly preferred. • Experience enabling AI/ML or natural ...

Fox

Senior Media Platform Engineer

Tempe, AZ

ABOUT THE ROLE Our Senior Media Platform Engineer role will build and operate the workflow ... Partner with AI/ML stakeholders to evaluate model options (build vs buy vs fine-tune), including ...

IntraEdge

Cloud Platform Engineer

Scottsdale, AZ · Hybrid

$56.25 - $75.25/hr

AI/ML experience preferred. Location: Scottsdale, AZ (Hybrid) Required Qualification (4-8 Yrs) * Strong experience in Kubernetes and GCP * Strong experience in IaC , Terraform , GitHub Actions, helm

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Required Qualifications: 5 years experience in DevOps, CloudOps, or ML Ops. 5 years experience with GCP AIML services (Vertex AI, AI Platform, BigQuery ML) or AWS ML services (SageMaker etc). 5 years ...

Redolent, Inc.

AI/ML Engineer

Phoenix, AZ · On-site

AI/ML Engineer Location: Phoenix, AZ Experience Level: 8+ years Rate: We are seeking a highly ... Cloud Platforms : Working knowledge of Google Cloud and Azure. * Front-End Frameworks/Libraries

YO AI Labs

AI/ML Engineer - Remote

Phoenix, AZ · Remote

$200 - $350/hr

AI/ML Engineer Job Type: Full-Time Location: Remote Job Summary We are seeking an experienced AI/ML ... You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to ...

IntraEdge

Senior AI/ML & IVR Engineer GCP

Scottsdale, AZ · On-site

$105K - $145K/yr

As a Senior AI/ML, IVR, and GCP Engineer, you will architect, develop, and optimize advanced AI/ML solutions and voice automation (IVR) platforms using Google Cloud Platform. You will work closely ...

Conch Technologies Inc

Avaya Engineer ( AI/ML )

Phoenix, AZ · On-site

$96K - $132K/yr

Avaya Engineer ( AI/ML ) Location: Phoenix, AZ, Charlotte, NC, and Sunrise, FL ( Onsite 5 days a ... Experience with Five9 Contact Center Platform * Experience with contact center call routing and ...

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All JobsMl Platform Engineer JobsMl Platform Engineer Jobs in Arizona

Ml Platform Engineer information

See Arizona salary details

$30

$59

$88

How much do ml platform engineer jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ml platform engineer in Arizona is $59.60, according to ZipRecruiter salary data. Most workers in this role earn between $47.02 and $68.75 per hour, depending on experience, location, and employer.

What is an ML Platform Engineer?

ML Platform Engineers are specialized software engineers who design, build, and maintain the infrastructure and tools needed to support the development, deployment, and scaling of machine learning models. They bridge the gap between data science and production engineering by automating model training, monitoring, versioning, and serving. Their work enables data scientists to focus on modeling while ensuring that ML solutions are reliable, reproducible, and scalable in real-world environments.

What skills and qualifications are needed to thrive as an ML Platform Engineer?

To thrive as an ML Platform Engineer, you need a strong background in computer science, software engineering, and machine learning concepts, often supported by a degree in a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), containerization (Docker, Kubernetes), CI/CD pipelines, and knowledge of ML frameworks (TensorFlow, PyTorch) are commonly required. Collaboration, problem-solving, and strong communication skills help you work efficiently with data scientists, engineers, and stakeholders. These skills ensure the development, scalability, and reliability of robust ML infrastructure that empowers teams to deploy and manage models effectively.

How does an ML Platform Engineer typically collaborate with data scientists and software engineers within a company?

ML Platform Engineers work closely with both data scientists and software engineers to streamline the process of developing, deploying, and maintaining machine learning models. They provide the infrastructure and tools necessary for data scientists to build and experiment with models efficiently, while ensuring seamless integration with production systems managed by software engineers. Regular communication, participation in cross-functional meetings, and shared project management tools are common ways teams collaborate. This close collaboration helps to bridge the gap between research and production, ensuring robust, scalable, and reliable ML solutions.

What is the difference between Ml Platform Engineer vs Data Scientist?

AspectML Platform EngineerData Scientist
Required credentialsBachelor's/Master's in CS, Engineering, or related; experience with cloud platformsBachelor's/Master's in Statistics, Math, or CS; strong programming skills
Work environmentBuilds and maintains ML infrastructure, collaborates with engineering teamsAnalyzes data, develops models, and interprets results
Industry usageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, tech firms, data-driven organizations

ML Platform Engineers focus on developing and maintaining the infrastructure that supports machine learning models, while Data Scientists primarily analyze data and build models. Both roles often collaborate but serve different functions within the AI and data ecosystem.

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

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

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

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

What cities in Arizona are hiring for Ml Platform Engineer jobs?

Cities in Arizona with the most Ml Platform Engineer job openings:

Ml Platform Engineer jobs near you
Infographic showing various Ml Platform Engineer job openings in Arizona as of August 2026, with employment types broken down into 55% Full Time, 43% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $123,965 per year, or $59.6 per hour.

Kubernetes/Google Cloud Platform Engineer (Only W2)

Trispark Inc

Scottsdale, AZ • On-site

$56.50 - $75.50/hr

Other

Posted 6 days ago

Job description

Kubernetes/Google Cloud Platform Engineer

Duration: 12 Months (Contract to perm)
Pay Rate: 50/HR
Work Mode: Hybrid
Interview Type:  Not Mentioned 

Ropes Test: Yes
Location: 

Scottsdale, Arizona 85260

Position Overview

We are seeking a Kubernetes / Google Cloud Platform Engineer with deep hands-on expertise in Google Cloud Platform, infrastructure automation, and modern observability stacks. In this role, you will build and maintain resilient cloud infrastructure, drive CI/CD and IaC best practices, support production systems through effective incident triage, and help integrate AI/ML concepts and AIOps into operational workflows.

Required Qualifications
  • Cloud & Platform Engineering: Strong experience with Google Cloud Platform (Google Cloud Platform) and Google Kubernetes Engine (GKE).
  • Infrastructure as Code & CI/CD: Strong experience in IaC using Terraform, Helm chart management, and CI/CD automation with GitHub Actions.
  • Programming & Scripting: Proficiency in Python, Ansible, and Node.js for automation, integration, and tooling.
  • Observability & Monitoring: Strong experience with the Prometheus and Grafana observability stack.
  • Core Systems & Networking: Solid understanding of Linux systems administration and networking fundamentals.
  • Operations & Incident Response: Proven experience in incident management, on-call support, production triage, and hands-on automation for CI/CD pipelines.
  • AIOps & AI Concepts: Strong understanding of AI/ML concepts and AIOps practices, including model lifecycle, AI/ML monitoring, or AI-driven alerting.
Preferred Qualifications
  • Certifications: Google Cloud Certified Professional Cloud Architect and/or Certified Kubernetes Administrator (CKA).
  • Software Engineering: Experience in Java/J2EE and Spring Boot applications.
  • MLOps & AI Infrastructure: Experience supporting or operating ML/AI platforms, pipelines (MLOps), GPU-based workloads, or ML infrastructure on Google Cloud Platform.
  • ML Platforms & Frameworks: Knowledge of Kubeflow, Vertex AI, or cloud-native ML pipelines.
  • Advanced AIOps & Automation: Exposure to AIOps tools, anomaly detection, predictive analytics systems, and integrating AI-driven automation directly into monitoring and incident response.
  • Distributed Systems: Experience working with large-scale distributed systems and microservices architecture.

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