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Ml Engineer Jobs in Arizona (NOW HIRING)

Confiz Limited

Principal AI Engineer

Phoenix, AZ · On-site

$180 - $230/hr

Design and architect AI/ML solutions, including LLM-based applications, agentic systems, and ... Collaborate with data engineers, ML engineers, full-stack developers, and product owners to ...

Pwc

ERP AI Engineer - Manager

Phoenix, AZ

$99K - $232K/yr

As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and ...

Master Electronics

Data Scientist II

Phoenix, AZ

Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and ...

Vangard, Inc.

AI/ML Product Manager

Scottsdale, AZ

Partner closely with engineering, data science, design, risk, legal, and business stakeholders to design, build, and improve AI/ML technical solutions. * Translate market research, user insights, and ...

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Showing results 21-40

All JobsMl Engineer JobsMl Engineer Jobs in Arizona

Ml Engineer information

See Arizona salary details

$30.8K

$83.1K

$132.3K

How much do ml engineer jobs pay per year?

As of Aug 24, 2026, the average yearly pay for ml engineer in Arizona is $83,109.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $101,600.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.

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

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

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

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

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

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

What cities in Arizona are hiring for Ml Engineer jobs?

Cities in Arizona with the most Ml Engineer job openings:

Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Arizona as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $83,109 per year, or $40 per hour.

Principal AI Engineer

Phoenix, AZ • On-site

Confiz Limited
IT Services • 501 - 1,000 employees
Learn more about Confiz Limitedexternal

$180 - $230/hr

Other

Posted 19 days ago

Job description

Confiz is seeking a Principal AI Engineer in the Phoenix AZ market, who can design and drive end-to-end AI-powered solutions from data engineering and model architecture to full-stack integration and deployment. This role bridges data platforms, AI/ML systems, and application development, ensuring solutions are scalable, secure, and production-ready.

Responsibilities
  • Design and architect AI/ML solutions, including LLM-based applications, agentic systems, and predictive models, aligned with business objectives.
  • Define data architecture and pipelines using Databricks (Delta Lake, Unity Catalog, MLflow) for large-scale data processing and model training/serving.
  • Architect full-stack solutions that integrate AI models into web/enterprise applications — covering front-end, back-end APIs, and cloud infrastructure.
  • Evaluate and select appropriate AI frameworks, LLM providers (OpenAI, Anthropic, Azure AI Foundry, etc.), and vector databases for use-case fit.
  • Establish best practices for model lifecycle management: versioning, monitoring, retraining, and governance.
  • Collaborate with data engineers, ML engineers, full-stack developers, and product owners to translate business requirements into technical architecture.
  • Design scalable, secure, and cost-optimized cloud architectures (Azure/AWS/GCP) for AI workloads.
  • Conduct architecture reviews, POCs, and technical feasibility assessments for new AI initiatives.
  • Mentor engineering teams on AI integration patterns, prompt engineering, RAG pipelines, and agentic workflows.
  • Ensure solutions meet performance, security, and compliance standards (data privacy, responsible AI practices).
Requirements
  • 10+ years in software/solution architecture, with 4+ years specifically in AI/ML architecture.
  • AI/ML: Strong understanding of LLMs, RAG architectures, agentic AI systems, prompt engineering, model fine-tuning, and MLOps.
  • Databricks: Hands-on experience with Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow, Databricks Workflows), Spark-based data processing.
  • Full-Stack Development: Working knowledge of front-end (React/Angular) and back-end (Node.js/.NET/Python) development, API design (REST/GraphQL), and microservices architecture.
  • Cloud Platforms: Experience with Azure (AI Foundry, Cognitive Services) and/or AWS/GCP AI & data services.
  • Data Engineering: Familiarity with ETL/ELT pipelines, data modeling, and data governance.
  • Programming: Python (mandatory), plus exposure to SQL, and at least one full-stack language (JavaScript/TypeScript, C#, or Java).
  • Architecture: Proven experience designing scalable, distributed systems; solid grasp of system design principles, security, and DevOps/CI-CD practices.
  • Strong stakeholder communication skills — ability to translate technical architecture into business value for both technical and non-technical audiences.
Nice to Have
  • Experience with vector databases (Pinecone, Weaviate, Snowflake Cortex).
  • Exposure to containerization (Docker/Kubernetes) and infrastructure-as-code (Terraform/Bicep).
  • Prior experience in a client-facing or pre-sales/solutioning capacity.
  • Certifications in Azure/AWS AI or Databricks (Databricks Certified Data Engineer/ML Associate).

We have a global team of amazing individuals working on highly innovative enterprise projects & products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast growth fintech, and multiple Silicon Valley startups.

What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.

People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.

To know more about Confiz Limited, visit https://www.linkedin.com/company/confiz/

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