AI ML Engineering Visa Sponsorship Jobs in Arizona
Arizona's AI and ML engineering market is anchored by Intel's semiconductor operations in Chandler, Apple and Amazon's expanding tech campuses in the Phoenix metro, and a growing aerospace and defense sector that increasingly relies on machine learning systems. Banner Health and other major healthcare networks also hire AI engineers to develop clinical decision tools.
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Are you ready to take the next step in your career? Join us for an exciting opportunity at Albertsons Companies, where innovation and customer service go hand-in-hand!
At Albertsons Companies, we are looking for someone who’s not just seeking a job, but someone who wants to make an impact. In this role, you’ll have the opportunity to lead, innovate, and contribute to the growth of a company that values great service and lasting customer relationships. This position offers the chance to work in a fast-paced, dynamic environment that’s constantly evolving.
This role is an individual contributor position responsible for designing, developing, fine-tuning, and operationalizing AI/ML capabilities for the AIOps platform within the Observability product. The candidate will work closely with the Lead Engineer, SRE teams, Platform team, Data Ingestion team, Platform DevOps team, Visualization team, and other portfolio teams.
As part of the AIOps Platform team, you will design and build intelligent systems that improve observability, incident response, and operational efficiency. This includes developing machine learning models for forecasting, anomaly prediction, alert classification, event intelligence, and causal analysis, as well as building AI agents and multi-agent workflows for RCA summarization, investigative assistance, and SRE productivity use cases.
This position will be based out of Phoenix, Arizona or Pleasanton CA.
Main responsibilities:
- Design, develop, and productionize AI/ML capabilities for the AIOps platform to support intelligent observability and operational decision-making.
- Build machine learning systems for time-series forecasting, anomaly prediction, incident prediction, alert classification, noise reduction, and event correlation.
- Develop causal ML and statistical inference solutions to identify likely root causes, dependency impacts, and relationships across systems and services.
- Create and fine-tune models for incident intelligence use cases such as forecasting service degradation, capacity risk prediction, alert prioritization, and anomaly explanation.
- Design feature pipelines and model training workflows using telemetry, log, metric, trace, topology, and incident data.
- Build intelligent RCA summarization capabilities using LLMs and agentic frameworks such as LangChain and LangGraph.
- Develop AI agents and multi-agent systems for use cases such as Multi-Agent RCA, SRE Assistant, remediation guidance, incident triage, and operational knowledge retrieval.
- Design prompt orchestration, reasoning workflows, retrieval pipelines, tool usage patterns, and memory/context handling for AI agents.
- Integrate AI/ML services with observability platforms, event systems, knowledge bases, CMDB, incident management tools, and automation platforms.
- Collaborate with platform and engineering teams to build scalable model-serving and agent-serving architectures.
- Define and implement evaluation frameworks for model quality, agent effectiveness, hallucination reduction, relevance, and operational usefulness.
- Ensure AI/ML systems are scalable, reliable, explainable, and aligned with enterprise security, governance, and responsible AI practices.
- Build and maintain APIs and microservices for model inference, online scoring, batch predictions, and agent orchestration.
- Partner with SREs, observability engineers, and product stakeholders to translate operational pain points into ML and AI-driven solutions.
- Continuously improve model performance, feature quality, inference latency, agent reliability, and business impact through experimentation and monitoring.
- Establish engineering best practices for ML development, prompt engineering, evaluation, model deployment, testing, versioning, and documentation.
- Support production incident analysis for AI/ML services and drive root cause identification and remediation for model or agent failures.
- Create technical documentation covering model design, feature logic, training pipelines, evaluation metrics, deployment architecture, and agent workflows.
Drive innovation in AI-enabled observability, causal intelligence, and agentic SRE workflows to enhance the value of the AIOps platform.
We are searching for someone with the following skills:
- Strong experience designing and building AI/ML systems for real-world production use cases.
- Solid hands-on experience with Python and common ML frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, Pandas, and NumPy.
- Experience building machine learning solutions for forecasting, anomaly detection, prediction, classification, clustering, ranking, or recommendation problems.
- Strong understanding of time-series modeling techniques for forecasting and operational prediction use cases.
- Experience with alert classification, incident prediction, event deduplication, prioritization, or signal correlation in observability or IT operations contexts.
- Knowledge of causal ML, causal inference, graph-based reasoning, and dependency-aware analysis techniques for RCA and impact analysis.
- Hands-on experience building AI applications using LLM frameworks such as LangChain and LangGraph.
- Experience designing AI agents or multi-agent systems for reasoning, summarization, task orchestration, troubleshooting, or assistant workflows.
- Strong understanding of prompt engineering, RAG architecture, embeddings, vector stores, tool calling, memory handling, and agent evaluation techniques.
- Experience integrating LLM systems with enterprise tools, APIs, knowledge repositories, and operational systems.
- Experience building backend services and APIs for AI/ML model inference and agent orchestration.
- Good understanding of observability data such as logs, metrics, traces, topology, incidents, and alerts.
- Experience with data engineering concepts including feature engineering, data preprocessing, model pipelines, and batch or streaming inference.
- Familiarity with graph databases such as Neo4j and their use in dependency mapping, causal analysis, and knowledge-driven AI systems.
- Experience with REST APIs, microservices architecture, Docker, Kubernetes, and cloud-native deployment patterns.
- Familiarity with CI/CD, MLOps, model lifecycle management, experiment tracking, and model versioning practices.
- Knowledge of OpenTelemetry, monitoring systems, and observability platforms is highly desirable.
- Strong understanding of software engineering fundamentals, system design, and scalable architecture patterns.
- Strong analytical and problem-solving skills, with the ability to convert ambiguous operational problems into measurable AI/ML solutions.
- Excellent communication and collaboration skills to work with SREs, platform engineers, product owners, and business stakeholders.
- Self-driven mindset with strong curiosity, innovation, and the ability to learn and apply emerging AI techniques effectively.
We believe the successful candidate has these qualifications and experience:
- Bachelor’s degree in computer science, Information Systems, Engineering, Data Science, Artificial Intelligence, or a related field, or equivalent practical experience.
- 6 to 10 plus years of overall experience in software engineering, machine learning, or AI system development.
- 3 plus years of hands-on experience building and deploying machine learning systems in production.
- Strong experience in Python-based AI/ML development is required.
- Experience working on observability, monitoring, or AIOps-related platforms is strongly preferred.
- Experience building LLM-powered applications, AI agents, or multi-agent workflows for enterprise use cases is highly preferred.
- Experience in AIOps, Observability, SRE, IT operations, or incident management domains.
- Experience applying AI/ML to RCA, anomaly explanation, incident summarization, service health prediction, or remediation recommendations.
- Familiarity with knowledge graphs and graph-based ML techniques for dependency-aware intelligence.
- Experience using vector databases and retrieval frameworks for enterprise search and agentic applications.
- Experience integrating AI services with tools such as ServiceNow, Grafana, Prometheus, Splunk, AppDynamics, or similar platforms.
Familiarity with MCP-based client or agent integrations is a plus.
We also provide a variety of benefits including:
- Competitive wages paid weekly
- Access to up to 50% of your earned wages before payday, via our partnership with Stream
- Associate discounts
- Health and financial well-being benefits for eligible associates (Medical, Dental, 401k and more!)
- Time off (vacation, holidays, sick pay). For eligibility requirements please visit myACI Benefits
- Leaders invested in your training, career growth and development
- An inclusive work environment with talented colleagues who reflect the communities we serve
Pay Transparency:
Starting rates will be no less than the local minimum wage and may vary based on criteria such as location, experience, and qualifications. Candidates with unique qualifications may be considered for compensation above this range. Benefits may include medical, dental, vision, disability and life insurance, sick pay, PTO/Vacation Pay or Flexible Time Off, paid holidays, bereavement pay, and retirement benefits (pension and/or 401k eligibility). Associates in this position may be eligible for a quarterly bonus.
Albertsons Companies is at the forefront of the revolution in retail. Committed to innovation and fostering a culture of belonging, our team is united with a unique purpose: to bring people together around the joys of food and to inspire well-being. We want talented individuals to be part of this journey!
Locally great and nationally strong, Albertsons Companies (NYSE: ACI) is a leading food and drug retailer in the U.S. We operate over 2,200 stores, 1,732 pharmacies, 405 fuel centers, 22 distribution facilities, and 19 manufacturing plants across 34 states and the District of Columbia. Our well-known banners include Albertsons, Safeway, Vons, Jewel-Osco, ACME, Shaw’s, Tom Thumb, United Supermarkets, United Express, Randalls, Albertson’s Market, Pavilions, Star Markets, Market Street, Carrs, Haggen, Lucky, Amigos, Andronico’s Community Markets, King’s, Balducci’s, and Albertson’s Market Street.
Our vision is to be a retail leader admired for national strength with deep local roots, offering an easy, fun, friendly, and inspiring experience, no matter how customers choose to shop with us. We celebrate the rich diversity of the communities we serve, and strive to create a workplace where everyone has equal access to opportunities and resources, and can fully contribute to their and our company’s success.
Bring your flavor
Building the future of food and well-being starts with you. Join our team and bring your best self to the table.
Disclaimer
The above statements are intended to describe the general nature of work performed by the employees assigned to this job and are not the official job description for the position. All employees must comply with Company, Division, and Store policies and applicable laws. The responsibilities, duties, and skills of personnel may vary within store and/or from store to store and the official job description will be provided during the application process.
Albertsons is an Equal Opportunity Employer
This Company is an Equal Opportunity Employer, and does not discriminate on the basis of race, gender, ethnicity, religion, national origin, age, disability, veteran status, gender identity/expression, sexual orientation, or on any other basis prohibited by law. Consistent with applicable state and local law, the Company will consider for employment qualified applicants with arrest and conviction records.
We endeavor to make this site accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at 1-888-255-2269(option #4).
Why choose us?
Are you ready to take the next step in your career? Join us for an exciting opportunity at Albertsons Companies, where innovation and customer service go hand-in-hand!
At Albertsons Companies, we are looking for someone who’s not just seeking a job, but someone who wants to make an impact. In this role, you’ll have the opportunity to lead, innovate, and contribute to the growth of a company that values great service and lasting customer relationships. This position offers the chance to work in a fast-paced, dynamic environment that’s constantly evolving.
This role is an individual contributor position responsible for designing, developing, fine-tuning, and operationalizing AI/ML capabilities for the AIOps platform within the Observability product. The candidate will work closely with the Lead Engineer, SRE teams, Platform team, Data Ingestion team, Platform DevOps team, Visualization team, and other portfolio teams.
As part of the AIOps Platform team, you will design and build intelligent systems that improve observability, incident response, and operational efficiency. This includes developing machine learning models for forecasting, anomaly prediction, alert classification, event intelligence, and causal analysis, as well as building AI agents and multi-agent workflows for RCA summarization, investigative assistance, and SRE productivity use cases.
This position will be based out of Phoenix, Arizona or Pleasanton CA.
Main responsibilities:
- Design, develop, and productionize AI/ML capabilities for the AIOps platform to support intelligent observability and operational decision-making.
- Build machine learning systems for time-series forecasting, anomaly prediction, incident prediction, alert classification, noise reduction, and event correlation.
- Develop causal ML and statistical inference solutions to identify likely root causes, dependency impacts, and relationships across systems and services.
- Create and fine-tune models for incident intelligence use cases such as forecasting service degradation, capacity risk prediction, alert prioritization, and anomaly explanation.
- Design feature pipelines and model training workflows using telemetry, log, metric, trace, topology, and incident data.
- Build intelligent RCA summarization capabilities using LLMs and agentic frameworks such as LangChain and LangGraph.
- Develop AI agents and multi-agent systems for use cases such as Multi-Agent RCA, SRE Assistant, remediation guidance, incident triage, and operational knowledge retrieval.
- Design prompt orchestration, reasoning workflows, retrieval pipelines, tool usage patterns, and memory/context handling for AI agents.
- Integrate AI/ML services with observability platforms, event systems, knowledge bases, CMDB, incident management tools, and automation platforms.
- Collaborate with platform and engineering teams to build scalable model-serving and agent-serving architectures.
- Define and implement evaluation frameworks for model quality, agent effectiveness, hallucination reduction, relevance, and operational usefulness.
- Ensure AI/ML systems are scalable, reliable, explainable, and aligned with enterprise security, governance, and responsible AI practices.
- Build and maintain APIs and microservices for model inference, online scoring, batch predictions, and agent orchestration.
- Partner with SREs, observability engineers, and product stakeholders to translate operational pain points into ML and AI-driven solutions.
- Continuously improve model performance, feature quality, inference latency, agent reliability, and business impact through experimentation and monitoring.
- Establish engineering best practices for ML development, prompt engineering, evaluation, model deployment, testing, versioning, and documentation.
- Support production incident analysis for AI/ML services and drive root cause identification and remediation for model or agent failures.
- Create technical documentation covering model design, feature logic, training pipelines, evaluation metrics, deployment architecture, and agent workflows.
Drive innovation in AI-enabled observability, causal intelligence, and agentic SRE workflows to enhance the value of the AIOps platform.
We are searching for someone with the following skills:
- Strong experience designing and building AI/ML systems for real-world production use cases.
- Solid hands-on experience with Python and common ML frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, Pandas, and NumPy.
- Experience building machine learning solutions for forecasting, anomaly detection, prediction, classification, clustering, ranking, or recommendation problems.
- Strong understanding of time-series modeling techniques for forecasting and operational prediction use cases.
- Experience with alert classification, incident prediction, event deduplication, prioritization, or signal correlation in observability or IT operations contexts.
- Knowledge of causal ML, causal inference, graph-based reasoning, and dependency-aware analysis techniques for RCA and impact analysis.
- Hands-on experience building AI applications using LLM frameworks such as LangChain and LangGraph.
- Experience designing AI agents or multi-agent systems for reasoning, summarization, task orchestration, troubleshooting, or assistant workflows.
- Strong understanding of prompt engineering, RAG architecture, embeddings, vector stores, tool calling, memory handling, and agent evaluation techniques.
- Experience integrating LLM systems with enterprise tools, APIs, knowledge repositories, and operational systems.
- Experience building backend services and APIs for AI/ML model inference and agent orchestration.
- Good understanding of observability data such as logs, metrics, traces, topology, incidents, and alerts.
- Experience with data engineering concepts including feature engineering, data preprocessing, model pipelines, and batch or streaming inference.
- Familiarity with graph databases such as Neo4j and their use in dependency mapping, causal analysis, and knowledge-driven AI systems.
- Experience with REST APIs, microservices architecture, Docker, Kubernetes, and cloud-native deployment patterns.
- Familiarity with CI/CD, MLOps, model lifecycle management, experiment tracking, and model versioning practices.
- Knowledge of OpenTelemetry, monitoring systems, and observability platforms is highly desirable.
- Strong understanding of software engineering fundamentals, system design, and scalable architecture patterns.
- Strong analytical and problem-solving skills, with the ability to convert ambiguous operational problems into measurable AI/ML solutions.
- Excellent communication and collaboration skills to work with SREs, platform engineers, product owners, and business stakeholders.
- Self-driven mindset with strong curiosity, innovation, and the ability to learn and apply emerging AI techniques effectively.
We believe the successful candidate has these qualifications and experience:
- Bachelor’s degree in computer science, Information Systems, Engineering, Data Science, Artificial Intelligence, or a related field, or equivalent practical experience.
- 6 to 10 plus years of overall experience in software engineering, machine learning, or AI system development.
- 3 plus years of hands-on experience building and deploying machine learning systems in production.
- Strong experience in Python-based AI/ML development is required.
- Experience working on observability, monitoring, or AIOps-related platforms is strongly preferred.
- Experience building LLM-powered applications, AI agents, or multi-agent workflows for enterprise use cases is highly preferred.
- Experience in AIOps, Observability, SRE, IT operations, or incident management domains.
- Experience applying AI/ML to RCA, anomaly explanation, incident summarization, service health prediction, or remediation recommendations.
- Familiarity with knowledge graphs and graph-based ML techniques for dependency-aware intelligence.
- Experience using vector databases and retrieval frameworks for enterprise search and agentic applications.
- Experience integrating AI services with tools such as ServiceNow, Grafana, Prometheus, Splunk, AppDynamics, or similar platforms.
Familiarity with MCP-based client or agent integrations is a plus.
We also provide a variety of benefits including:
- Competitive wages paid weekly
- Access to up to 50% of your earned wages before payday, via our partnership with Stream
- Associate discounts
- Health and financial well-being benefits for eligible associates (Medical, Dental, 401k and more!)
- Time off (vacation, holidays, sick pay). For eligibility requirements please visit myACI Benefits
- Leaders invested in your training, career growth and development
- An inclusive work environment with talented colleagues who reflect the communities we serve
Pay Transparency:
Starting rates will be no less than the local minimum wage and may vary based on criteria such as location, experience, and qualifications. Candidates with unique qualifications may be considered for compensation above this range. Benefits may include medical, dental, vision, disability and life insurance, sick pay, PTO/Vacation Pay or Flexible Time Off, paid holidays, bereavement pay, and retirement benefits (pension and/or 401k eligibility). Associates in this position may be eligible for a quarterly bonus.
Albertsons Companies is at the forefront of the revolution in retail. Committed to innovation and fostering a culture of belonging, our team is united with a unique purpose: to bring people together around the joys of food and to inspire well-being. We want talented individuals to be part of this journey!
Locally great and nationally strong, Albertsons Companies (NYSE: ACI) is a leading food and drug retailer in the U.S. We operate over 2,200 stores, 1,732 pharmacies, 405 fuel centers, 22 distribution facilities, and 19 manufacturing plants across 34 states and the District of Columbia. Our well-known banners include Albertsons, Safeway, Vons, Jewel-Osco, ACME, Shaw’s, Tom Thumb, United Supermarkets, United Express, Randalls, Albertson’s Market, Pavilions, Star Markets, Market Street, Carrs, Haggen, Lucky, Amigos, Andronico’s Community Markets, King’s, Balducci’s, and Albertson’s Market Street.
Our vision is to be a retail leader admired for national strength with deep local roots, offering an easy, fun, friendly, and inspiring experience, no matter how customers choose to shop with us. We celebrate the rich diversity of the communities we serve, and strive to create a workplace where everyone has equal access to opportunities and resources, and can fully contribute to their and our company’s success.
Bring your flavor
Building the future of food and well-being starts with you. Join our team and bring your best self to the table.
Disclaimer
The above statements are intended to describe the general nature of work performed by the employees assigned to this job and are not the official job description for the position. All employees must comply with Company, Division, and Store policies and applicable laws. The responsibilities, duties, and skills of personnel may vary within store and/or from store to store and the official job description will be provided during the application process.
Albertsons is an Equal Opportunity Employer
This Company is an Equal Opportunity Employer, and does not discriminate on the basis of race, gender, ethnicity, religion, national origin, age, disability, veteran status, gender identity/expression, sexual orientation, or on any other basis prohibited by law. Consistent with applicable state and local law, the Company will consider for employment qualified applicants with arrest and conviction records.
We endeavor to make this site accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at 1-888-255-2269(option #4).
AI ML Engineering Job Roles in Arizona
See all 246+ AI ML Engineering Jobs in Arizona
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Search AI ML Engineering Jobs in ArizonaAI ML Engineering Jobs in Arizona: Frequently Asked Questions
Which companies sponsor visas for AI ML engineers in Arizona?
Intel in Chandler is one of the most active H-1B visa sponsors for AI and ML engineering roles in Arizona. Amazon, Apple, and Microsoft all have significant Phoenix-area operations that sponsor these positions. Defense contractors like Raytheon and Honeywell Aerospace, both headquartered or heavily staffed in Tucson and the Phoenix metro, also file H-1B petitions for ML engineers working on embedded systems and computer vision applications.
Which visa types are most common for AI ML engineering roles in Arizona?
The H-1B is the most common visa category for AI and ML engineering roles in Arizona, as these positions typically require at least a bachelor's degree in computer science, electrical engineering, or a related field, satisfying the specialty occupation requirement. Candidates with extraordinary ability in AI research may pursue the O-1A. Those with U.S. master's or PhD degrees may also be prioritized through the H-1B advanced degree exemption, which has a separate 20,000-slot allocation.
Which cities in Arizona have the most AI ML engineering sponsorship jobs?
The Phoenix metro area, including Chandler, Tempe, and Scottsdale, concentrates the largest share of AI and ML engineering sponsorship jobs in Arizona, driven by Intel's semiconductor campus, major tech company outposts, and a dense cluster of fintech and healthtech startups. Tucson has a smaller but active market, supported by Raytheon, Honeywell Aerospace, and the University of Arizona's research programs, particularly in computer vision and autonomous systems.
How to find ai ml engineering visa sponsorship jobs in Arizona?
Migrate Mate filters job listings specifically to roles where employers have a documented history of visa sponsorship, so you're not sorting through postings that won't support international candidates. For AI and ML engineering roles in Arizona, you can narrow results by location to target Phoenix metro companies like Intel and Amazon or Tucson-based defense contractors. Migrate Mate's filters help you focus on roles aligned with your visa category and experience level.
Are there university pipelines or industry considerations specific to AI ML engineering sponsorship in Arizona?
Arizona State University and the University of Arizona both produce significant AI and ML engineering talent and have established relationships with regional employers that sponsor OPT and H-1B visas. ASU's partnership with companies in the Intel semiconductor corridor in Chandler creates a direct pipeline for international graduates. Defense and aerospace employers in Arizona sometimes require security clearances, which can affect sponsorship timelines since clearance eligibility is restricted to U.S. citizens and certain permanent residents.
What is the prevailing wage for sponsored ai ml engineering 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.