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Mlops Machine Learning Engineer Jobs in Phoenix, AZ

Design, build, and deploy machine learning pipelines and end-to-end AI solutions using GCP services ... Implement robust MLOps for model monitoring, versioning, CI/CD, retraining, and performance ...

Lead ML Ops Engineer

Tempe, AZ · On-site

$98K - $129K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

This role manages a team of Machine Learning Operations Engineers, oversees the endtoend machinelearning strategy and execution, sets vision for MLOps, and ensures alignment with business goals. How ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Tempe, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Phoenix, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Stay current with emerging trends in Machine Learning, Generative AI, Agentic AI, and MLOps Required Skills * Strong Python programming with frameworks such as PyTorch, TensorFlow, or scikit-learn

Machine Learning Tutor

Gilbert, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Mesa, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ... MLOps practices including versioning, CI/CD, monitoring, and drift detection. · Implement data ...

... engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning ... AI, MLOps, or related machine learning frameworks. * Experience developing, deploying, and ...

Vice President, AI Engineering

Scottsdale, AZ · On-site

$210 - $368/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Lead AI engineering, applied AI, machine learning engineering, platform engineering, automation, architecture, MLOps, and related technical teams responsible for building, integrating, and supporting ...

Showing results 41-60

Mlops Machine Learning Engineer information

See Phoenix, AZ salary details

$31.3K

$127.9K

$192.1K

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

As of Aug 14, 2026, the average yearly pay for mlops machine learning engineer in Phoenix, AZ is $127,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

Senior AI/ML & IVR Engineer GCP

IntraEdge

Scottsdale, AZ

$105K - $145K/yr

Full-time

Re-posted 25 days ago


Job description

Position Overview:
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 with data scientists, engineers, and product teams to drive innovation and build scalable machine learning and conversational AI systems.

Key Responsibilities:

  • Design, build, and deploy machine learning pipelines and end-to-end AI solutions using GCP services (BigQuery, Vertex AI, Dataflow, Pub/Sub, etc.)

  • Architect and optimize IVR/Conversational AI systems integrating speech recognition, NLP, and dialog management

  • Implement robust MLOps for model monitoring, versioning, CI/CD, retraining, and performance optimization on GCP

  • Lead technical projects, mentor team members, and ensure best practices in code quality, security, and AI ethics

  • Collaborate with cross-functional teams to integrate AI/ML and IVR capabilities with business applications and customer experiences

  • Develop APIs and cloud-native interfaces for scalable, secure, low-latency access to AI features

  • Ensure compliance and data governance for voice and customer data according to privacy and regulatory standards

Must-Have Skills:

  • Expertise with GCP AI/ML tools (Vertex AI, BigQuery ML, Kubeflow, Dataflow, Cloud Functions)

  • Strong coding skills in Python and/or Java, with experience in ML frameworks (TensorFlow, PyTorch, scikit-learn)

  • Experience building and scaling IVR/Conversational AI systems (Dialogflow, Contact Center AI, Twilio, etc.)

  • Advanced MLOps: CI/CD, containerization (Docker), orchestration (Kubernetes), monitoring, and automation

  • Data engineering skills: ETL/ELT, real-time and batch pipelines

  • Excellent communication, collaboration, and technical leadership abilities

  • Bachelor's degree (minimum), Master's or PhD preferred, in Computer Science, Engineering, or related field

  • 7+ years of experience in AI/ML engineering, cloud platforms, and IVR/conversational applications

Desirable:

  • GCP Professional Certifications (Data Engineer, ML Engineer)

  • Experience with call center, telecom, or enterprise voice automation

  • Knowledge of infrastructure-as-code (Terraform, Cloud Deployment Manager)

Success in This Role:

  • Reliable, high-performance deployment of AI/ML and IVR solutions on GCP

  • Measurable improvements in automation, customer experience, and efficiency

  • Effective collaboration with business, engineering, and product teams


Position Overview:
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 with data scientists, engineers, and product teams to drive innovation and build scalable machine learning and conversational AI systems.

Key Responsibilities:

  • Design, build, and deploy machine learning pipelines and end-to-end AI solutions using GCP services (BigQuery, Vertex AI, Dataflow, Pub/Sub, etc.)

  • Architect and optimize IVR/Conversational AI systems integrating speech recognition, NLP, and dialog management

  • Implement robust MLOps for model monitoring, versioning, CI/CD, retraining, and performance optimization on GCP

  • Lead technical projects, mentor team members, and ensure best practices in code quality, security, and AI ethics

  • Collaborate with cross-functional teams to integrate AI/ML and IVR capabilities with business applications and customer experiences

  • Develop APIs and cloud-native interfaces for scalable, secure, low-latency access to AI features

  • Ensure compliance and data governance for voice and customer data according to privacy and regulatory standards

Must-Have Skills:

  • Expertise with GCP AI/ML tools (Vertex AI, BigQuery ML, Kubeflow, Dataflow, Cloud Functions)

  • Strong coding skills in Python and/or Java, with experience in ML frameworks (TensorFlow, PyTorch, scikit-learn)

  • Experience building and scaling IVR/Conversational AI systems (Dialogflow, Contact Center AI, Twilio, etc.)

  • Advanced MLOps: CI/CD, containerization (Docker), orchestration (Kubernetes), monitoring, and automation

  • Data engineering skills: ETL/ELT, real-time and batch pipelines

  • Excellent communication, collaboration, and technical leadership abilities

  • Bachelor's degree (minimum), Master's or PhD preferred, in Computer Science, Engineering, or related field

  • 7+ years of experience in AI/ML engineering, cloud platforms, and IVR/conversational applications

Desirable:

  • GCP Professional Certifications (Data Engineer, ML Engineer)

  • Experience with call center, telecom, or enterprise voice automation

  • Knowledge of infrastructure-as-code (Terraform, Cloud Deployment Manager)

Success in This Role:

  • Reliable, high-performance deployment of AI/ML and IVR solutions on GCP

  • Measurable improvements in automation, customer experience, and efficiency

  • Effective collaboration with business, engineering, and product teams

Education:Employment Type: FULL_TIME

IntraEdge logo

About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

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