Machine Learning Engineer Visa Sponsorship Jobs in Oregon
Oregon's machine learning engineer market centers on Portland's growing tech sector, with employers like Nike, Intel, and Adidas running data science operations alongside cloud-focused startups. Corvallis adds university-adjacent research opportunities through Oregon State University. Visa sponsorship is available across both established tech firms and emerging AI companies throughout the state.
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Get Access To All JobsINTRODUCTION
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
ABOUT QUANTIPHI
Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.
Company Highlights:
- Quantiphi has seen 2.5x growth YoY since its inception in 2013, we don't just innovate—we lead.
- Headquartered in Boston, with 4000+ Quantiphi professionals across the globe.
- As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been recognized with:
- 17x Google Cloud Partner of the Year awards in the last 8 years
- 3x AWS AI/ML award wins
- 3x NVIDIA Partner of the Year titles
- 2x Snowflake Partner of the Year awards
- We have also garnered Top analyst recognitions from Gartner, ISG, and Everest Group.
- We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.
- We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.
Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here!
JOB OVERVIEW
We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML model development, and end-to-end deployment. The ideal candidate will have hands-on experience with Google Cloud Document AI, Vertex AI, and Large Language Models (LLMs). You will be responsible for designing, training, evaluating, and fine-tuning ML models, integrating them with cloud-based applications, and ensuring scalable and reliable performance in production environments.
KEY RESPONSIBILITIES:
- Design, develop, train, and fine-tune machine learning models, including custom and pre-trained models on Google Cloud Vertex AI and Document AI.
- Build and manage custom Document AI processors such as Custom Document Splitter, Custom Document Classifier, and Custom Document Extractor.
- Work with pre-trained Document AI processors and customize them for business-specific document understanding tasks.
- Develop and deploy ML solutions using GCP services like Cloud Functions, Cloud Run, Firestore, Cloud SQL, Cloud Storage, and BigQuery.
- Design and implement data preprocessing pipelines for large-scale, unstructured, and semi-structured data.
- Integrate ML models into production systems via secure and scalable APIs.
- Evaluate model performance using standard ML metrics, perform model validation, and optimize for accuracy, latency, and efficiency.
- Collaborate with cross-functional teams (Data Engineers, Software Developers, and Product Teams) to ensure seamless model integration and delivery.
- Troubleshoot and debug ML pipelines, training jobs, and model deployment issues.
- Maintain proper version control of code, models, and configurations using Git/GitHub.
- Follow best practices for ML lifecycle management, testing, and documentation.
BASIC QUALIFICATIONS (ESSENTIAL):
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
- Proven experience with Google Cloud Document AI (Custom Workbench: Splitter, Classifier, Extractor, and pre-trained processors).
- Hands-on experience with Google Cloud Vertex AI for model training, tuning, and deployment.
- Strong understanding and practical experience with Large Language Models (LLMs) and their fine-tuning.
- Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with ML model design, training, testing, evaluation, and fine-tuning.
- Solid experience in data preprocessing and feature engineering.
- Familiarity with GCP services such as Cloud Functions, Cloud Run, Firestore, Cloud Storage, Cloud SQL, and BigQuery.
- Strong understanding of API integration for ML model deployment.
- Proficiency in troubleshooting and debugging ML-related issues.
- Experience with Git/GitHub for version control and collaboration.
OTHER QUALIFICATIONS (GOOD TO HAVE):
- Knowledge of MLOps practices for automating ML workflows, model versioning, and continuous deployment.
- Experience building and exposing ML models via FastAPI or similar frameworks.
- Familiarity with data pipeline orchestration tools (e.g., Airflow, Kubeflow).
- Understanding of security and compliance best practices in ML systems.
- Strong analytical, problem-solving, and communication skills.
WHAT IS IN IT FOR YOU:
- Be part of the fastest-growing AI-first digital transformation and engineering company in the world
- Be a leader of an energetic team of highly dynamic and talented individuals
- Exposure to working with fortune 500 companies and innovative market disruptors
- Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
INTRODUCTION
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
ABOUT QUANTIPHI
Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.
Company Highlights:
- Quantiphi has seen 2.5x growth YoY since its inception in 2013, we don't just innovate—we lead.
- Headquartered in Boston, with 4000+ Quantiphi professionals across the globe.
- As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been recognized with:
- 17x Google Cloud Partner of the Year awards in the last 8 years
- 3x AWS AI/ML award wins
- 3x NVIDIA Partner of the Year titles
- 2x Snowflake Partner of the Year awards
- We have also garnered Top analyst recognitions from Gartner, ISG, and Everest Group.
- We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.
- We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.
Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here!
JOB OVERVIEW
We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML model development, and end-to-end deployment. The ideal candidate will have hands-on experience with Google Cloud Document AI, Vertex AI, and Large Language Models (LLMs). You will be responsible for designing, training, evaluating, and fine-tuning ML models, integrating them with cloud-based applications, and ensuring scalable and reliable performance in production environments.
KEY RESPONSIBILITIES:
- Design, develop, train, and fine-tune machine learning models, including custom and pre-trained models on Google Cloud Vertex AI and Document AI.
- Build and manage custom Document AI processors such as Custom Document Splitter, Custom Document Classifier, and Custom Document Extractor.
- Work with pre-trained Document AI processors and customize them for business-specific document understanding tasks.
- Develop and deploy ML solutions using GCP services like Cloud Functions, Cloud Run, Firestore, Cloud SQL, Cloud Storage, and BigQuery.
- Design and implement data preprocessing pipelines for large-scale, unstructured, and semi-structured data.
- Integrate ML models into production systems via secure and scalable APIs.
- Evaluate model performance using standard ML metrics, perform model validation, and optimize for accuracy, latency, and efficiency.
- Collaborate with cross-functional teams (Data Engineers, Software Developers, and Product Teams) to ensure seamless model integration and delivery.
- Troubleshoot and debug ML pipelines, training jobs, and model deployment issues.
- Maintain proper version control of code, models, and configurations using Git/GitHub.
- Follow best practices for ML lifecycle management, testing, and documentation.
BASIC QUALIFICATIONS (ESSENTIAL):
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
- Proven experience with Google Cloud Document AI (Custom Workbench: Splitter, Classifier, Extractor, and pre-trained processors).
- Hands-on experience with Google Cloud Vertex AI for model training, tuning, and deployment.
- Strong understanding and practical experience with Large Language Models (LLMs) and their fine-tuning.
- Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with ML model design, training, testing, evaluation, and fine-tuning.
- Solid experience in data preprocessing and feature engineering.
- Familiarity with GCP services such as Cloud Functions, Cloud Run, Firestore, Cloud Storage, Cloud SQL, and BigQuery.
- Strong understanding of API integration for ML model deployment.
- Proficiency in troubleshooting and debugging ML-related issues.
- Experience with Git/GitHub for version control and collaboration.
OTHER QUALIFICATIONS (GOOD TO HAVE):
- Knowledge of MLOps practices for automating ML workflows, model versioning, and continuous deployment.
- Experience building and exposing ML models via FastAPI or similar frameworks.
- Familiarity with data pipeline orchestration tools (e.g., Airflow, Kubeflow).
- Understanding of security and compliance best practices in ML systems.
- Strong analytical, problem-solving, and communication skills.
WHAT IS IN IT FOR YOU:
- Be part of the fastest-growing AI-first digital transformation and engineering company in the world
- Be a leader of an energetic team of highly dynamic and talented individuals
- Exposure to working with fortune 500 companies and innovative market disruptors
- Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Machine Learning Engineer Job Roles in Oregon
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Search Machine Learning Engineer Jobs in OregonMachine Learning Engineer Jobs in Oregon: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in Oregon?
Intel is one of Oregon's largest sponsors of H-1B visas for technical roles, operating major facilities in Hillsboro. Nike's global headquarters in Beaverton has an active data science division. Adidas North America, Daimler Trucks North America, and a growing number of Portland-based AI startups have also filed H-1B petitions for machine learning positions. Sponsorship patterns vary by company size, budget cycle, and current headcount needs.
Which visa types are most common for machine learning engineer roles in Oregon?
The H-1B is by far the most common visa for machine learning engineers in Oregon, given that the role requires at least a bachelor's degree in computer science, statistics, or a closely related field. Australians may qualify for the E-3 visa, and Canadians and Mexicans may qualify under TN visa status using the engineer or computer systems analyst categories. O-1A visas apply for engineers with demonstrated extraordinary ability.
How to find machine learning engineer visa sponsorship jobs in Oregon?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search for machine learning engineer roles in Oregon without wading through positions that won't support an international hire. Employers in Portland, Hillsboro, and Beaverton post regularly. Filtering by role and state on Migrate Mate surfaces active openings at companies with a documented history of sponsoring technical talent.
Which cities in Oregon have the most machine learning engineer sponsorship jobs?
Portland is Oregon's primary tech hub and accounts for the largest share of machine learning engineer openings. Hillsboro, home to Intel's large semiconductor campus, generates significant demand for applied ML and data infrastructure roles. Beaverton sees activity through Nike and adjacent tech employers. Corvallis is smaller but relevant for candidates interested in research-oriented roles connected to Oregon State University's computing programs.
Are there any Oregon-specific considerations for machine learning engineers seeking visa sponsorship?
Oregon does not impose a state-level income tax surcharge on visa-sponsored workers, but employers must still meet Department of Labor prevailing wage requirements tied to the specific metro area. Portland's wage determinations differ from those in Hillsboro or Eugene, so job title and work location both affect the wage floor on an H-1B petition. Oregon State University and Portland State University are active pipelines, meaning some employers are already familiar with international hiring through OPT and CPT programs.
What is the prevailing wage for sponsored machine learning engineer jobs in Oregon?
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.