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Google Cloud Machine Learning Engineer Jobs in Oregon

AI Solutions Engineering Delivery Lead

Portland, OR · On-site

$108K - $143K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... cloud platforms such as AWS, Azure, or Google Cloud Platform, with cloud foundational ...

OR · On-site

$205K - $355K/yr

Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform * Collect and gather ...

OR

$466K - $750K/yr

We are looking for an experienced Machine Learning Engineer with deep expertise in training and inference efficiency for Large Language Models (LLMs), Multimodal LLMs, and other media ML models. In ...

$122K - $200K/yr

Overview LMI is seeking a Cloud Engineer to support our LIGER platform to meet specific customer ... Design and deploy solutions within Google Cloud Platform environments, including project/org ...

Senior Forward Deployed Engineer- AWS

Portland, OR · On-site

$110K - $152K/yr

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ...

Lead Forward Deployed Engineer - AWS

Portland, OR · On-site

$108K - $143K/yr

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ...

Strong understanding of Google Cloud Platform (GCP) services including BigQuery, Cloud Storage ... Experience building and operationalizing machine learning solutions using Model Studio, pro-code ...

OR · On-site

Support deployment of AI services across AWS, Azure, or Google Cloud using containerized and cloud ... or machine learning applications. * Strong programming experience in Python. * Experience ...

OR · On-site

You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to ... Build scalable, production-quality machine learning workflows and pipelines using cloud ...

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ...

OR · On-site

$170K - $334K/yr

Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform * Collect and gather ...

OR · On-site

$523K - $920K/yr

The Localization Data Science and Engineering team is at the forefront of removing language ... We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and ...

Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore ... Google Professional Machine Learning Engineer certification or the equivalent ML certification.

General Information

Portland, OR · On-site

$91K - $115K/yr

Partner with engineering, product, finance, and business stakeholders to connect technical ... Google Cloud. * Awareness of AI, machine learning, generative AI, data platforms, and AI-enabled ...

Build and integrate AI-enabled capabilities into applications, including machine learning models ... Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with relational ...

Showing results 41-60

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.

AI Solutions Engineering Delivery Lead

Pwc

Portland, OR • On-site

$108K - $143K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

27th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Internal Firm Services - Other

Management Level

Director

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
Translating the vision, you set the tone, and inspire others to follow. Your role is crucial in driving business growth, shaping the direction of client engagements, and mentoring the next generation of leaders. You are expected to be a guardian of PwC's reputation, understanding that quality, integrity, inclusion and a commercial mindset are all foundational to our success. You create a healthy working environment while maximising client satisfaction. You cultivate the potential in others and actively team across the PwC Network, understanding tradeoffs, and leveraging our collective strength.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Lead in line with our values and brand.
Develop new ideas, solutions, and structures; drive thought leadership.
Solve problems by exploring multiple angles and using creativity, encouraging others to do the same.
Balance long-term, short-term, detail-oriented, and big picture thinking.
Make strategic choices and drive change by addressing system-level enablers.
Promote technological advances, creating an environment where people and technology thrive together.
Identify gaps in the market and convert opportunities to success for the Firm.
Adhere to and enforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance) the Firm's code of conduct, and independence requirements.
The Opportunity
:
The AI Solutions Engineering Delivery Lead will oversee multiple multidisciplinary teams consisting of data scientists, software engineers, front-end developers, and other specialists in the design, development, deployment, monitoring, and maintenance of full-stack AI solutions. As a senior technical leader, you will leverage deep technical specialization, strategic vision, comprehensive business acumen, and exceptional stakeholder communication skills to deliver impactful AI-driven solutions. This is a "hand-on" overseeing one or more AI solution work streams, driving continuous adaptation to emerging technologies, ensuring rigorous quality standards, and fostering a culture of continuous improvement and innovation.
Responsibilities
:
- Provide strategic and technical leadership across multiple AI solution delivery teams
- Architect and oversee the delivery of comprehensive AI solutions, emphasizing full-stack development, including integration of Large Language Models (LLMs) and orchestrated applications
- Manage and own the full lifecycle of AI models and solutions, from development through deployment, monitoring, maintenance, and iterative enhancement
- Direct experiment-driven development, ensuring rapid prototyping, testing, validation, and operational excellence
- Establish and drive consistent quality control and continuous improvement of AI solutions, closely collaborating with business stakeholders to align solutions with strategic objectives
- Develop and maintain robust stakeholder relationships, clearly communicating complex solutions and strategic implications to senior business leaders
- Promote technical innovation, process improvement, and effective methodologies across teams
- Continuously evaluate and drive adoption of emerging technologies to enhance solution capabilities and maintain competitive advantage
What You Must Have
:
- Bachelor's Degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field
- Minimum of 10 years of experience, including substantial experience in a senior technical leadership role managing multiple multidisciplinary teams
What Sets You Apart
:
- An advanced degree is preferred
- Proven track record of hands-on experience in architecting, delivering, and managing AI and machine learning solutions, particularly with orchestrated LLM applications
- Proven specialization in Python, Pandas, Scikit-learn, PyTorch, Langchain, Semantic Kernel, SQL, vector DBs, LLMs, and prompt engineering
- Proven specialization with major cloud platforms such as AWS, Azure, or Google Cloud Platform, with cloud foundational certifications highly desirable
- Extensive experience with Agile methodologies, continuous integration/continuous deployment (CI/CD), Git version control, and rigorous testing frameworks (unit, integration, end-to-end)
- Extensive experience translating complex technical solutions into strategic business outcomes
- Prior experience leveraging executive-level communication skills, capable of effectively articulating technical and strategic concepts to multiple stakeholders while navigating ambiguity
- Proven track record of leading strategy, emphasizing analytical, decision-making, and problem-solving capabilities
- Proven ability to navigate complexity and ambiguity, providing clear direction and maintaining composure under pressure

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $122,500 - $423,780. For residents of Washington state the salary range for this position is: $122,500 - $504,500. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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