Machine Learning Visa Sponsorship Jobs in Oregon
Oregon's machine learning job market is anchored by Nike's global headquarters in Beaverton, Intel's major semiconductor campus in Hillsboro, and a growing Portland tech corridor that includes companies like Daimler Trucks North America and Vacasa. Many of these employers have established H-1B visa sponsorship track records, making Oregon a realistic target for international machine learning engineers and research scientists.
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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 Job Roles in Oregon
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Search Machine Learning Jobs in OregonMachine Learning Jobs in Oregon: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Oregon?
Intel is among the most active H-1B sponsors in Oregon, regularly filing for machine learning and AI engineering roles at its Hillsboro campus. Nike, headquartered in Beaverton, sponsors machine learning engineers who work on sports analytics and consumer personalization. Smaller Oregon-based tech firms and SaaS companies in Portland have also filed LCAs for machine learning positions, though sponsorship volume varies considerably by company size and hiring cycle.
Which visa types are most common for machine learning roles in Oregon?
The H-1B is the primary visa category for machine learning professionals in Oregon, as these roles consistently meet the specialty occupation standard given their degree requirements in computer science, statistics, or a directly related field. Candidates with outstanding research credentials may qualify for the O-1A. International students completing graduate programs at Oregon State University or the University of Oregon often use OPT and STEM OPT extension periods to bridge toward employer sponsorship.
Which cities in Oregon have the most machine learning sponsorship jobs?
Portland and the broader metro area, including Beaverton and Hillsboro, account for the large majority of machine learning sponsorship activity in Oregon. Hillsboro is particularly notable because Intel's semiconductor R&D operations generate consistent demand for applied ML and data science talent. Eugene has a smaller but emerging presence, partly driven by University of Oregon research affiliations. Salem and other smaller Oregon cities have minimal machine learning sponsorship activity.
How to find machine learning visa sponsorship jobs in Oregon?
Migrate Mate filters machine learning jobs specifically by sponsorship availability and state, making it straightforward to browse verified Oregon openings without sorting through roles that don't support visa candidates. You can search by job title and location to surface Intel, Nike, and Portland-area tech employers currently hiring. Because Oregon's machine learning market is concentrated in a handful of metro areas, filtering by city alongside role type gives the most targeted results.
Are there any state-specific considerations for machine learning roles in Oregon that international candidates should know?
Oregon does not impose a state income tax surcharge specific to visa holders, and Portland's tech corridor has a relatively strong university pipeline from Oregon State University's computer science and AI programs, which employers often recruit from directly. Machine learning roles in Oregon tend to cluster in semiconductor hardware ML at Intel and applied consumer analytics at Nike, so candidates with domain experience in those areas may find their profile aligns well with the state's dominant employers.
What is the prevailing wage for sponsored machine learning 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.