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Google Cloud Machine Learning Engineer Jobs in Oregon

Cresta

Staff Machine Learning Engineer

OR · On-site +1

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 ...

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 ...

May Mobility

Lead Machine Learning Engineer

OR · On-site +1

$102K - $134K/yr

Practical experience handling the "Long Tail" problem in Machine Learning. * Strong programming skills in Python/PyTorch in a Linux environment. * Functional understanding of LiDAR, Camera and Radar ...

Nvidia

Machine Learning Engineer, AI Safety

OR · On-site +1

We are looking for a talented Machine Learning Engineer to work on Product Security, Content Safety, ML Fairness and Robustness efforts for LLMs across all of our research and production engineering ...

SentinelOne

Principal AI Engineering Architect

OR · On-site +1

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 ...

The Avian Consulting LLC

MLOps Engineer

Portland, OR · On-site

... manage machine learning models in production environments. • Develop scalable data and model ... Azure, or Google Cloud Platform). • Experience with Infrastructure as Code tools such as ...

Pwc

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

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Google Cloud Machine Learning Engineer information

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

As of Sep 2, 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 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 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 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.

Staff Machine Learning Engineer

Cresta

OR • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 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:

  • Define and lead the technical vision for Cresta's next-generation Agentic AI systems, including Agentic Assist and enterprise AI Agents.
  • Architect scalable, production-grade LLM systems that integrate reasoning, retrieval, planning, tool use, and real-time decision-making into cohesive, intelligent workflows.
  • Design and evolve multi-agent orchestration frameworks that combine RAG, structured knowledge, domain-adapted models, and automated actions.
  • Establish best practices for building robust, reliable, and cost-efficient LLM-powered systems in high-scale production environments.
  • Own evaluation strategy for complex, non-deterministic AI systems, including offline benchmarking, online experimentation, LLM-as-a-judge methodologies, and systematic failure analysis.
  • Proactively identify and mitigate agent failure modes such as hallucinations, tool misuse, retrieval errors, prompt brittleness, context drift, and multi-step reasoning breakdowns.
  • Define measurable quality standards (accuracy, faithfulness, task completion, latency, cost efficiency, robustness) and drive continuous system improvement.
  • Influence cross-team architecture decisions across ML, backend, and product engineering to ensure seamless integration of AI capabilities.
  • Mentor senior engineers, raise the technical bar, and contribute to long-term AI strategy and roadmap planning.
  • Translate cutting-edge research advances into practical, high-impact production systems.

Qualifications We Value:

  • Bachelor's degree in Computer Science, Mathematics, or a related field; Master's or Ph.D. strongly preferred.
  • 7+ years of experience building and deploying machine learning systems in production, including deep hands-on experience with LLMs at scale.
  • Demonstrated leadership in architecting complex AI systems, particularly agentic or multi-step LLM workflows.
  • Deep expertise in transformer-based models, embeddings, retrieval systems, and Retrieval-Augmented Generation (RAG) pipelines.
  • Experience designing evaluation frameworks for LLM systems beyond single-turn prompts, including robustness testing and production monitoring.
  • Strong systems thinking: ability to design for scalability, latency constraints, cost efficiency, security, and long-term maintainability.
  • Extensive experience with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Proven ability to influence technical direction across teams as a senior individual contributor.
  • A strong bias toward action - able to prototype rapidly while maintaining production rigor.

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.

OTE Range: $230,000-$300,000 + Offers Equity

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