Machine Learning Visa Sponsorship Jobs in Michigan
Michigan's machine learning job market centers on Detroit's automotive tech sector, Ann Arbor's university-driven research ecosystem, and Grand Rapids' growing health tech industry. Companies like Ford, General Motors, and the University of Michigan regularly hire ML engineers and sponsor work visas. Strong demand spans autonomous vehicle systems, predictive analytics, and computer vision applications.
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Get Access To All JobsINTRODUCTION
We Miracle Software Systems is looking for the ML Engineer (Generative AI) on W2/Full-time.
ROLE AND RESPONSIBILITIES
Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions — including Generative AI and Large Language Model (LLM) systems — in areas such as computer vision, perception, localization, natural language processing, and conversational AI. They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in experimental methodologies, statistics, prompt engineering, and coding for tool building and analysis. Design and develop innovative ML models, Gen AI systems, and software algorithms — including LLM-based architectures (e.g., transformer models, RAG pipelines, fine-tuned foundation models) — to solve complex business problems in both structured and unstructured environments.
BASIC QUALIFICATIONS
- Skills:
- GCP Compute Engine
- GCP Cloud Storage
- GCP IAM
- GCP Cloud Functions
- Google Kubernetes Engine (GKE)
- Cloud SQL
- Pub/Sub
- Vertex AI
- Dataflow
- Cloud Composer (Airflow)
- BigQuery ML
- Python
- SQL
-
Apache Spark
-
Skills Required:
- GCP – Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions. For example, designing and implementing a cloud-native application architecture using GKE (Google Kubernetes Engine) with Cloud SQL and Pub/Sub.
- Big Data – Experience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery. For example, building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics.
- Data Warehousing – Experience designing and maintaining data warehouse solutions (e.g., BigQuery, Snowflake, Redshift). For example, modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior.
- Artificial Intelligence & Expert Systems – Experience developing or integrating AI/ML models and rule-based expert systems. For example, building a classification model using Vertex AI to predict customer churn, or implementing a rule engine that automates underwriting decisions.
- API – Experience designing, building, and consuming RESTful or gRPC APIs. For example, developing a versioned REST API with OAuth 2.0 authentication that serves as the integration layer between a mobile application and backend microservices.
PREFERRED QUALIFICATIONS
- Skills Preferred:
-
Google Cloud Platform – Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer (Airflow), and BigQuery ML. For example, using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.
-
Experience Required:
-
Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. 10+ years in IT; 8+ years in development
-
Experience Preferred:
- Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
- Proven experience in building and deploying RAG systems, including the use of Vector Databases.
- Proficiency in Python programming.
- Solid experience with SQL for data manipulation and querying.
- Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML.
- Basic understanding and practical experience with Machine Learning model fine-tuning.
- Familiarity with data engineering concepts and practices.
- Expertise in prompt engineering techniques for interacting with LLMs.
- Experience with the OpenAI SDK.
- Experience developing robust APIs, preferably with FastAPI.
- Proficiency with version control systems (e.g., Git).
- Experience with containerization technologies (e.g., Docker).
LOCATION
Dearborn, MI
COMPENSATION
- Job Type: W2/Full-time
- Long term
INTRODUCTION
We Miracle Software Systems is looking for the ML Engineer (Generative AI) on W2/Full-time.
ROLE AND RESPONSIBILITIES
Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions — including Generative AI and Large Language Model (LLM) systems — in areas such as computer vision, perception, localization, natural language processing, and conversational AI. They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in experimental methodologies, statistics, prompt engineering, and coding for tool building and analysis. Design and develop innovative ML models, Gen AI systems, and software algorithms — including LLM-based architectures (e.g., transformer models, RAG pipelines, fine-tuned foundation models) — to solve complex business problems in both structured and unstructured environments.
BASIC QUALIFICATIONS
- Skills:
- GCP Compute Engine
- GCP Cloud Storage
- GCP IAM
- GCP Cloud Functions
- Google Kubernetes Engine (GKE)
- Cloud SQL
- Pub/Sub
- Vertex AI
- Dataflow
- Cloud Composer (Airflow)
- BigQuery ML
- Python
- SQL
-
Apache Spark
-
Skills Required:
- GCP – Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions. For example, designing and implementing a cloud-native application architecture using GKE (Google Kubernetes Engine) with Cloud SQL and Pub/Sub.
- Big Data – Experience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery. For example, building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics.
- Data Warehousing – Experience designing and maintaining data warehouse solutions (e.g., BigQuery, Snowflake, Redshift). For example, modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior.
- Artificial Intelligence & Expert Systems – Experience developing or integrating AI/ML models and rule-based expert systems. For example, building a classification model using Vertex AI to predict customer churn, or implementing a rule engine that automates underwriting decisions.
- API – Experience designing, building, and consuming RESTful or gRPC APIs. For example, developing a versioned REST API with OAuth 2.0 authentication that serves as the integration layer between a mobile application and backend microservices.
PREFERRED QUALIFICATIONS
- Skills Preferred:
-
Google Cloud Platform – Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer (Airflow), and BigQuery ML. For example, using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.
-
Experience Required:
-
Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. 10+ years in IT; 8+ years in development
-
Experience Preferred:
- Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
- Proven experience in building and deploying RAG systems, including the use of Vector Databases.
- Proficiency in Python programming.
- Solid experience with SQL for data manipulation and querying.
- Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML.
- Basic understanding and practical experience with Machine Learning model fine-tuning.
- Familiarity with data engineering concepts and practices.
- Expertise in prompt engineering techniques for interacting with LLMs.
- Experience with the OpenAI SDK.
- Experience developing robust APIs, preferably with FastAPI.
- Proficiency with version control systems (e.g., Git).
- Experience with containerization technologies (e.g., Docker).
LOCATION
Dearborn, MI
COMPENSATION
- Job Type: W2/Full-time
- Long term
Machine Learning Job Roles in Michigan
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Search Machine Learning Jobs in MichiganMachine Learning Jobs in Michigan: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Michigan?
Ford Motor Company, General Motors, and Stellantis are among Michigan's most active visa sponsors for machine learning engineers, particularly for autonomous driving and predictive maintenance applications. The University of Michigan and Michigan State University sponsor ML researchers through academic positions. Health systems like Henry Ford Health and Beaumont Health also hire ML talent and have sponsored visas for specialized data science and clinical AI roles.
Which visa types are most common for machine learning roles in Michigan?
The H-1B is the most common visa for machine learning professionals in Michigan, given that ML engineering typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, statistics, or a related field. OPT and STEM OPT extensions are frequently used by graduates from University of Michigan and Michigan State before transitioning to H-1B sponsorship. Some research-focused roles at universities may use J-1 or O-1 visas.
Which cities in Michigan have the most machine learning sponsorship jobs?
Ann Arbor leads Michigan for machine learning sponsorship jobs, driven by University of Michigan spin-offs, automotive tech firms, and AI startups concentrated in the area. Detroit and its suburbs, including Dearborn and Troy, are strong for automotive-adjacent ML roles at Ford, GM, and Stellantis. Grand Rapids has a smaller but growing presence in health tech ML, and Lansing sees some activity tied to state government and Michigan State University.
How to find machine learning visa sponsorship jobs in Michigan?
Migrate Mate is designed specifically for international job seekers looking for visa sponsorship, and you can filter directly for machine learning roles in Michigan. This removes the guesswork of identifying which employers are open to sponsorship. Given Michigan's concentration in automotive tech and university research, filtering by industry can help you target the most active sponsoring employers in the state.
Are there state-specific considerations for machine learning professionals seeking sponsorship in Michigan?
Michigan's machine learning hiring is heavily shaped by the automotive industry's investment in autonomous vehicles and connected car technology, meaning ML roles here often require domain knowledge in sensor fusion, computer vision, or embedded systems rather than purely general ML skills. Ann Arbor's university ecosystem also creates a pipeline where academic research positions can transition to industry sponsorship. Employers filing H-1B petitions must meet Department of Labor prevailing wage requirements specific to Michigan's regional wage levels.
What is the prevailing wage for sponsored machine learning jobs in Michigan?
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.
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