ML Engineer Visa Sponsorship Jobs in Arizona
Arizona's ML engineer job market is concentrated in the Phoenix metro, where companies like Intel, Amazon, and Banner Health hire for machine learning roles across semiconductor, cloud, and healthcare AI verticals. Tucson adds university-driven demand through the University of Arizona. Employers across the state regularly sponsor H-1B visas for qualified ML engineers.
Find ML Engineer JobsOverview
Showing 5 of 11+ ML Engineer Jobs in Arizona with Visa Sponsorship
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all ML Engineer Jobs in Arizona with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer Jobs in Arizona with Visa Sponsorship.
Get Access To All JobsINTRODUCTION
What Cognite is: Relentless to achieve Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here. Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
ROLE AND RESPONSIBILITIES
We are seeking an AI Platform Engineer to join the Cognite Atlas AI Product team in Phoenix, AZ, to engineer, build, and operate the production-grade, multi-cloud platform that enables our internal and partner teams to build, deploy, and manage industrial AI agents. You will be responsible for creating the core services, frameworks, and infrastructure for our "agent builder workbench" and agent runtime, focusing on scalability, reliability, cost-efficiency, and security. Your work will directly impact industrial efficiency and sustainability, which is critical to our mission of powering a high-tech, sustainable, and profitable industrial future.
The Impact you bring to Cognite:
- Design, build, and maintain the core Python SDKs and services for the Atlas AI platform. Create clean abstractions that empower Solution Engineers to easily define and test agents and workflows.
- Build the core agentic runtime, ensuring it is scalable, meets its SLOs, and can reliably manage the state, orchestration, and execution of industrial agents.
- Develop a robust, governed, and secure framework for AI agent tool-use. Engineer the platform components that allow solution engineers to safely add new tools (e.g., API calls, database queries) and that manage the secure execution, monitoring, and access control for those tools.
- Manage the LLM serving layer, including deploying and optimizing models for low-latency/high-throughput inference. Build and maintain model routing logic to select the most appropriate model (e.g., performance vs. cost) for a given task.
- Implement evaluation and observability for all AI services. Create standardized frameworks for systematically evaluating the performance, accuracy, cost, and safety of LLMs and agentic workflows. Drive the implementation of robust, automated testing strategies for LLM-based systems.
- Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, participating in on-call rotations, and ensuring a fast and effective incident response process.
- Work closely with the Lead Architect to translate the technical vision into implemented, production-grade services. Act as a key partner for the Solution Engineers (your internal customers) to understand their needs and abstract common patterns into reusable, robust platform components.
- Stay up to date on the latest developments in the field, and mentor junior developers.
BASIC QUALIFICATIONS
- Bachelor's or Master’s degree in Computer Science or a related field, or equivalent practical experience.
- 8+ years of professional experience in backend software engineering, platform engineering, or MLOps, with a proven track record of architecting and operating complex systems at scale.
- 2+ years of hands-on experience building applications or platforms on top of AI/ML models or LLMs.
- Expert-level proficiency in Python and a strong background in software architecture, robust API design, and building maintainable, well-documented SDKs for other developers.
- Hands-on experience with Kubernetes (K8s) and building services on managed PaaS in a multi-cloud environment (AWS, Azure, GCP). Strong understanding of Infrastructure as Code (e.g., Terraform).
- Proven experience building and operating production-grade SaaS software. Understanding of the full development life cycle, including CI/CD, monitoring, telemetry, and on-call incident response.
- Practical experience with LLM orchestration frameworks (Bedrock, Vertex, Semantic Kernel, LangChain).
- Strong verbal and written communication skills, with the ability to articulate complex technical designs and decisions clearly.
PREFERRED QUALIFICATIONS
- Hands-on experience deploying and managing LLMs in production using high-performance serving frameworks.
- Experience with MLOps/LLMOps tools for tracing, monitoring, and evaluating LLM applications (LangSmith, Arize, Phoenix, or equivalent).
- Experience with RAG Infrastructure, embedding generation pipelines, vector database integrations, and high-performance vector similarity search APIs.
BENEFITS
A snapshot of our many perks and benefits as a Cogniter:
- Competitive compensation
- 401(k) with employer matching
- Competitive health, dental, vision & disability coverages for employees and all dependents
- Unlimited PTO
- Paid Parental Leave Program
- Employee Referral Program
- Join a team of 60+ different nationalities 🌐 with Diversity, Equality and Inclusion (DEI) in focus 🤝.
- A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @cognitedata 📷 to know more
- Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries
- Join our HUB 🗣️ to be part of the conversation directly with Cogniters and our partners.
- Paid mobile phone and WiFi
LOCATION
Location: Phoenix, AZ
Equal Opportunity
Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.
INTRODUCTION
What Cognite is: Relentless to achieve Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here. Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
ROLE AND RESPONSIBILITIES
We are seeking an AI Platform Engineer to join the Cognite Atlas AI Product team in Phoenix, AZ, to engineer, build, and operate the production-grade, multi-cloud platform that enables our internal and partner teams to build, deploy, and manage industrial AI agents. You will be responsible for creating the core services, frameworks, and infrastructure for our "agent builder workbench" and agent runtime, focusing on scalability, reliability, cost-efficiency, and security. Your work will directly impact industrial efficiency and sustainability, which is critical to our mission of powering a high-tech, sustainable, and profitable industrial future.
The Impact you bring to Cognite:
- Design, build, and maintain the core Python SDKs and services for the Atlas AI platform. Create clean abstractions that empower Solution Engineers to easily define and test agents and workflows.
- Build the core agentic runtime, ensuring it is scalable, meets its SLOs, and can reliably manage the state, orchestration, and execution of industrial agents.
- Develop a robust, governed, and secure framework for AI agent tool-use. Engineer the platform components that allow solution engineers to safely add new tools (e.g., API calls, database queries) and that manage the secure execution, monitoring, and access control for those tools.
- Manage the LLM serving layer, including deploying and optimizing models for low-latency/high-throughput inference. Build and maintain model routing logic to select the most appropriate model (e.g., performance vs. cost) for a given task.
- Implement evaluation and observability for all AI services. Create standardized frameworks for systematically evaluating the performance, accuracy, cost, and safety of LLMs and agentic workflows. Drive the implementation of robust, automated testing strategies for LLM-based systems.
- Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, participating in on-call rotations, and ensuring a fast and effective incident response process.
- Work closely with the Lead Architect to translate the technical vision into implemented, production-grade services. Act as a key partner for the Solution Engineers (your internal customers) to understand their needs and abstract common patterns into reusable, robust platform components.
- Stay up to date on the latest developments in the field, and mentor junior developers.
BASIC QUALIFICATIONS
- Bachelor's or Master’s degree in Computer Science or a related field, or equivalent practical experience.
- 8+ years of professional experience in backend software engineering, platform engineering, or MLOps, with a proven track record of architecting and operating complex systems at scale.
- 2+ years of hands-on experience building applications or platforms on top of AI/ML models or LLMs.
- Expert-level proficiency in Python and a strong background in software architecture, robust API design, and building maintainable, well-documented SDKs for other developers.
- Hands-on experience with Kubernetes (K8s) and building services on managed PaaS in a multi-cloud environment (AWS, Azure, GCP). Strong understanding of Infrastructure as Code (e.g., Terraform).
- Proven experience building and operating production-grade SaaS software. Understanding of the full development life cycle, including CI/CD, monitoring, telemetry, and on-call incident response.
- Practical experience with LLM orchestration frameworks (Bedrock, Vertex, Semantic Kernel, LangChain).
- Strong verbal and written communication skills, with the ability to articulate complex technical designs and decisions clearly.
PREFERRED QUALIFICATIONS
- Hands-on experience deploying and managing LLMs in production using high-performance serving frameworks.
- Experience with MLOps/LLMOps tools for tracing, monitoring, and evaluating LLM applications (LangSmith, Arize, Phoenix, or equivalent).
- Experience with RAG Infrastructure, embedding generation pipelines, vector database integrations, and high-performance vector similarity search APIs.
BENEFITS
A snapshot of our many perks and benefits as a Cogniter:
- Competitive compensation
- 401(k) with employer matching
- Competitive health, dental, vision & disability coverages for employees and all dependents
- Unlimited PTO
- Paid Parental Leave Program
- Employee Referral Program
- Join a team of 60+ different nationalities 🌐 with Diversity, Equality and Inclusion (DEI) in focus 🤝.
- A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @cognitedata 📷 to know more
- Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries
- Join our HUB 🗣️ to be part of the conversation directly with Cogniters and our partners.
- Paid mobile phone and WiFi
LOCATION
Location: Phoenix, AZ
Equal Opportunity
Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.
ML Engineer Job Roles in Arizona
See all ML Engineer Jobs in Arizona
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search ML Engineer Jobs in ArizonaML Engineer Jobs in Arizona: Frequently Asked Questions
Which companies sponsor visas for ML engineers in Arizona?
Intel's Chandler campus is one of Arizona's largest H-1B sponsors for technical roles, including machine learning engineers. Amazon Web Services, Microsoft, and PayPal maintain engineering operations in the Phoenix area and have documented sponsorship histories for ML positions. Banner Health and Dignity Health sponsor ML engineers building clinical AI tools. Defense contractors like Raytheon also hire ML engineers in Tucson, though sponsorship practices vary by clearance requirements.
Which visa types are most common for ML engineer roles in Arizona?
The H-1B is the primary visa category for ML engineers in Arizona, as the role consistently qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, mathematics, or a related field. Candidates already holding O-1A visas based on extraordinary ability in AI research also find strong employer interest in the Phoenix market. TN visa status is available to Canadian and Mexican nationals in qualifying computer-related occupations.
How to find ml engineer visa sponsorship jobs in Arizona?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to browse ML engineer roles in Arizona without sorting through positions that don't sponsor. You can narrow results to the Phoenix or Tucson metro areas and filter by employer type. Migrate Mate also surfaces companies with consistent sponsorship track records, which is especially useful for ML engineers targeting industries like semiconductor manufacturing, healthcare AI, or fintech.
Which cities in Arizona have the most ML engineer sponsorship jobs?
Phoenix and its East Valley cities, particularly Chandler, Scottsdale, and Tempe, account for the majority of ML engineer sponsorship activity in Arizona. Intel's Chandler semiconductor operations, Tempe's fintech cluster, and Scottsdale's growing tech corridor drive most of this demand. Tucson is a secondary market with ML hiring concentrated around the University of Arizona, defense contractors, and optical sciences companies like II-VI Incorporated.
Are there state-specific factors ML engineers should know about Arizona sponsorship hiring?
Arizona's cost of living relative to California tech hubs makes Phoenix an increasingly attractive location for employers expanding ML teams without Bay Area overhead, which has broadened the sponsorship market in recent years. The University of Arizona and Arizona State University produce ML graduate talent that feeds local pipelines, and some employers prefer candidates already embedded in the state's research ecosystem. Arizona has no state income tax on wages, which affects total compensation calculations but does not directly impact visa sponsorship eligibility.
What is the prevailing wage for sponsored ml engineer jobs in Arizona?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.