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Google Cloud Machine Learning Engineer Jobs in Oregon

OR · On-site

$134K - $180K/yr

... cloud technologies like AWS Lambdas and Google functions, etc.) * Exposure to all aspects of the ... a Machine Learning Engineer, ML Ops engineer, or related position). Education Requirements:

As a Machine Learning at BetterHelp, you'll join a diverse team of licensed clinicians, engineers, product pros, creatives, marketers, and business leaders who share a passion for expanding access to ...

OR · On-site

$104K - $143K/yr

... across cloud, on-prem, and edge compute environments * Work closely with autonomy researchers ... software engineering, machine learning engineering, MLOps, or related roles * Experience ...

Senior Machine Learning Engineer

OR · Remote

$140K - $190K/yr

Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy ... machine learning fundamentals (model selection, training, evaluation, feature engineering) and ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

To get there, we build agentic AI that combines the best of local and cloud intelligence - private ... Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research ...

$55.75 - $74.50/hr

AI-related certifications such as Google Cloud Certified - Professional Machine Learning Engineer are a plus What Success Looks Like * Secure, compliant cloud and AI platforms aligned to NYL ...

OR · On-site

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... cloud-based infrastructure. * Proven ability to influence technical direction across teams as a ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

OR · On-site

You will collaborate closely with clients, data scientists, data engineers, platform/DevOps teams ... Strong systems-level knowledge of network and cloud architecture, Linux-based operating systems ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Google Cloud Machine Learning Engineer information

See Oregon salary details

$24

$66

$92

How much do google cloud machine learning engineer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for google cloud machine learning engineer in Oregon is $66.49, according to ZipRecruiter salary data. Most workers in this role earn between $56.68 and $75.72 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning engineer?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What is the difference between Google Cloud Machine Learning Engineer vs Data Scientist?

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Oregon? For Google Cloud Machine Learning Engineer jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Oregon with the most Google Cloud Machine Learning Engineer job openings:
Infographic showing various Google Cloud Machine Learning Engineer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $138,295 per year, or $66.5 per hour.

Principal Machine Learning Engineer

iHerb

OR • On-site

$134K - $180K/yr

Other

Re-posted 7 days ago


iHerb rating

7.5

Company rating: 7.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz


Job description

Job Summary: 

The Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems and platforms that make an impact on millions of users. This role will work closely with business partners to provide machine intelligence driven solutions and products to simplify and enhance the customer experience and to automate core business processes. The Machine Learning Engineer will partner closely with Data Scientists, Applied Scientists, and Software Developers to ensure predictive models make business impact.

Job Expectations: 

  • Partner with the Data Platform team in a two-way exchange of best practices

  • Adopt common patterns and build effective abstractions across different machine learning pipelines that simplify existing machine learning processes and accelerate the modelling process from the business problem's inception to deploying a model solution into production

  • Develop horizontal solutions to robustly scale the team's machine learning models and processes

  • Build software with Object-oriented Design Patterns and Analysis (OOA and OOD) with an eye toward reducing technical debt and maintaining services at high availability

  • Participate in requirements reviews, design reviews, and code reviews

  • Research and prototype new technologies to support the rapid growth of the business

  • Interact cross-functionally with a wide variety of technical teams and work closely with data and applied scientists to identify opportunities to improve on iHerb's platform

The duties and responsibilities described above may provide only a partial description of this position. This is not an exhaustive list of all aspects of the job. Other duties and responsibilities not outlined in this document may be added as necessary or desirable, with or without notice.

Knowledge, Skills and Abilities:

   Required:

  • Strong coding experience (e.g. Java, C#, Python)

  • Experience with gathering data from multiple sources using big data technologies (Spark, Hadoop, BigQuery, Athena, etc.)

  • Experience building machine learning infrastructure following robust software engineering practices

  • Knowledge of modern software development tools, systems, and practices (design patterns, CI/CD, git, unit testing, smoke testing, integration testing, job schedulers, cloud technologies like AWS Lambdas and Google functions, etc.)

  • Exposure to all aspects of the software development life-cycle

  • Experience with messaging technologies (Kafka, Google Pub/Sub, Kinesis, RabbitMQ, etc.)

  • Experience with Docker and Kubernetes

  • High degree of accuracy and attention to detail

  • Excellent organization skills and ability to multitask

Equipment Knowledge: 

  • Experience with Microsoft Office Suite (Word, Excel, PowerPoint)

  • Experience with Google Business Suite (Gmail, Drive, Docs, Sheets, Forms) preferred

Experience Requirements:

Generally requires a minimum of two (2) years relevant experience in applied machine learning or machine learning systems/infrastructure, and one (1) year of relevant work experience in machine learning engineering or related fields. (e.g., as a Machine Learning Engineer, ML Ops engineer, or related position).

Education Requirements:

Bachelor's Degree in Computer Science, Electrical Engineering, or related field required, Masters Degree preferred.

Judgment/Reasoning Ability:  Able to identify, troubleshoot and resolve problems quickly using sound judgment, poise and diplomacy.  Ability to use judgment and reasoning skills, and determine when to escalate issues, as required, in a timely manner.

Physical Demands: The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job. While performing the duties of this job, the Team Member is regularly required to talk and hear. The Team Member is frequently required to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach with hands and arms.  Reaching above shoulder heights, below the waist or lifting as required to file documents or store materials throughout the work day. The Team Member may occasionally lift or move office products and supplies up to 25 pounds. Proper lifting techniques required.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Work Environment: The noise in the work environment is usually moderate. Other factors are:

  • Hectic, fast-paced with multi-level distractions

  • Professional, yet casual work environment

  • Office / Warehouse environment

  • Ability to work extended hours as required

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