ZipRecruiter

Log In

1

Google Cloud Machine Learning Engineer Jobs in Oregon

Cresta

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... cloud-based infrastructure. * Demonstrated ability to optimize real-time ML systems for performance ...

Upstart

Staff/Principal Machine Learning Engineer

OR · On-site +1

As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering-collaborating closely with Research Scientists, Data Scientists, and ML Platform ...

New York Life

$147K - $211K/yr

Cloud Architecture & Engineering * Lead the design and implementation of enterprisegrade solutions on Google Cloud Platform. * Develop and maintain cloud reference architectures and engineering ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

The Avian Consulting LLC

MLOps Engineer

Portland, OR · On-site

Deploy and manage machine learning models in production environments. * Develop scalable data and ... Google Cloud Platform). * Experience with Infrastructure as Code tools such as Terraform or ...

SentinelOne

OR · On-site

Deep expertise in building highly available, low-latency machine learning systems, including ... Google Cloud. Why SentinelOne? AI is redefining how the world operates and rewriting the rules of ...

Cotiviti

$125K - $172K/yr

Overview We are looking for a Senior Principal Machine Learning Engineer to lead the design and delivery of end-to-end ML/AI systems that turn vast volumes of claims, clinical, and member data into ...

previous pagenext page

Showing results 21-40

All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Oregon

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 job categories do people searching Google Cloud Machine Learning Engineer jobs in Oregon look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Oregon 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:
Google Cloud Machine Learning Engineer jobs near you
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.

Senior Machine Learning Engineer

Cresta

OR • On-site, Remote

$205K - $270K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago

Job description

About the role:

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include:

  • Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.
  • Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.
  • Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities:

  • Lead the design and development of Cresta's next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
  • Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.
  • Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
  • Improve reasoning, planning, and tool-use capabilities in real-world AI applications.
  • Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
  • Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.
  • Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.
  • Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.
  • Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta's platform.
  • Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta's AI systems.

Qualifications We Value:

  • Bachelor's degree in Computer Science, Mathematics, or a related field; Master's or Ph.D. preferred.
  • 5-8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
  • Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
  • Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
  • Experience building and evaluating complex agentic or multi-step LLM workflows.
  • Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.
  • Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Perks & Benefits:

We offer a comprehensive and people-first benefits package to support you at work and in life:

  • Comprehensive medical, dental, and vision coverage with plans to fit you and your family
  • Flexible PTO to take the time you need, when you need it
  • Paid parental leave for all new parents welcoming a new child
  • Retirement savings plan to help you plan for the future
  • Remote work setup budget to help you create a productive home office
  • Monthly wellness and communication stipend to keep you connected and balanced
  • In-office meal program and commuter benefits provided for onsite employees

Compensation at Cresta: 

Cresta's approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

Salary Range: $205,000-$270,000 + Offers Equity

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai 

Apply