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Google Software Engineer Jobs in Portland, OR (NOW HIRING)

You will work closely with data scientists, software engineers, and cloud teams to operationalize ... Google Cloud Platform). * Experience with Infrastructure as Code tools such as Terraform or ...

MTS-1, Android Engineer

Portland, OR · On-site

$118K - $205K/yr

... software development, working in teams with a mix of engineers and non-engineers. * 5+ years ... Please provide links to any apps you've published on the Google Play Store or open-source projects ...

Lead Forward Deployed Engineer, Palantir

Portland, OR · On-site

$108K - $143K/yr

... Google Cloud) The team AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and ...

Sr. DevOps Engineer

Portland, OR · On-site

$137K - $177K/yr

Manage and maintain our cloud-based infrastructure on Google Cloud Platform (GCP), ensuring high ... software, firmware and hardware throughout enterprise infrastructure. Eclypsium's SaaS platform ...

Sr. DevOps Engineer

Portland, OR

$137K - $177K/yr

Manage and maintain our cloud-based infrastructure on Google Cloud Platform (GCP), ensuring high ... software, firmware and hardware throughout enterprise infrastructure. Eclypsium's SaaS platform ...

Sr. DevOps Engineer

Portland, OR · On-site +1

$137K - $177K/yr

Manage and maintain our cloud-based infrastructure on Google Cloud Platform (GCP), ensuring high ... software, firmware and hardware throughout enterprise infrastructure. Eclypsium's SaaS platform ...

... Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus ...

Showing results 41-60

Google Software Engineer information

See Portland, OR salary details

$67.3K

$156.4K

$217.9K

How much do google software engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for google software engineer in Portland, OR is $156,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,300.00 and $183,500.00 per year, depending on experience, location, and employer.

What does a Google software engineer do?

Google Software Engineers typically work in cross-functional teams alongside product managers, UX designers, and other engineers. You'll regularly participate in code reviews, design discussions, and agile ceremonies to ensure the delivery of high-quality software. Collaboration often extends beyond the immediate team, offering opportunities to share knowledge, mentor peers, and contribute to company-wide technical initiatives. This team-oriented approach allows engineers to learn from different perspectives, accelerate their growth, and deliver more impactful solutions.

Does Google still hire software engineers?

Yes, Google continues to hire software engineers to support its technology development, product teams, and infrastructure. The company regularly posts job openings requiring skills in programming, data structures, and algorithms, often emphasizing experience with tools like Python, C++, or Java. Candidates typically go through a rigorous interview process that assesses technical expertise and problem-solving abilities.

What is a Google software engineer?

A Google Software Engineer is responsible for designing, developing, testing, and maintaining software solutions that power Google's products and services. They work on large-scale systems, collaborate with cross-functional teams, and use languages like C++, Java, and Python. Engineers at Google solve complex technical challenges and contribute to high-performance, scalable applications.

What are the key skills and qualifications needed to thrive as a Google software engineer?

To thrive as a Google Software Engineer, you need strong skills in computer science fundamentals, programming (particularly in languages like Java, C++, or Python), and a relevant degree or equivalent experience. Familiarity with advanced development tools, distributed systems, cloud infrastructure (such as Google Cloud Platform), and sometimes technical certifications is highly valued. Excellent problem-solving abilities, communication, and teamwork are standout soft skills in this environment. These skills are essential for building scalable products, collaborating in high-impact teams, and driving innovation at a large tech company.

Is it hard to get a software engineer job at Google?

Getting a software engineer position at Google is highly competitive due to the company's rigorous hiring process, which includes multiple technical interviews assessing coding skills, problem-solving, and system design. Candidates typically need strong programming abilities in languages like Python, Java, or C++, along with relevant experience and a solid understanding of algorithms and data structures.

What are the most commonly searched types of Google Software Engineer jobs in Portland, OR?

The most popular types of Google Software Engineer jobs in Portland, OR are:

What job categories do people searching Google Software Engineer jobs in Portland, OR look for?

The top searched job categories for Google Software Engineer jobs in Portland, OR are:

What cities near Portland, OR are hiring for Google Software Engineer jobs?

Cities near Portland, OR with the most Google Software Engineer job openings:

Infographic showing various Google Software Engineer job openings in Portland, OR as of August 2026, with employment types broken down into 80% Full Time, 16% Part Time, and 4% Contract. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $156,450 per year, or $75.2 per hour.

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Job Title: MLOps Engineer
Location: Portland, OR (5 days Onsite), they may ask for F2F client interview.

Job Description

We are seeking an experienced MLOps Engineer to join our team onsite in Portland, OR. The ideal candidate will be responsible for designing, deploying, automating, and maintaining machine learning pipelines and infrastructure. You will work closely with data scientists, software engineers, and cloud teams to operationalize ML models and ensure scalable, secure, and reliable AI/ML solutions.

Key Responsibilities

  • Design, build, and maintain end-to-end MLOps pipelines for model training, testing, deployment, and monitoring.
  • Automate ML workflows using CI/CD best practices.
  • Deploy and manage machine learning models in production environments.
  • Develop scalable data and model pipelines on cloud platforms.
  • Monitor model performance, data drift, and system health.
  • Collaborate with data scientists to productionize ML models.
  • Implement model versioning, experiment tracking, and artifact management.
  • Optimize infrastructure for performance, scalability, and cost efficiency.
  • Ensure security, governance, and compliance for ML platforms.
  • Troubleshoot production issues and improve operational reliability.

Required Skills

  • 5+ years of experience in DevOps, Data Engineering, or MLOps.
  • Strong experience with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
  • Experience with containerization technologies like Docker and Kubernetes.
  • Strong knowledge of CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
  • Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
  • Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
  • Knowledge of model monitoring, logging, and observability tools.
  • Strong understanding of Git version control and software development best practices.
  • Experience with Linux environments and shell scripting.

 

 

Preferred Qualifications

  • Experience with Generative AI, LLM deployment, or RAG-based applications.
  • Familiarity with Apache Airflow, Kafka, or Spark.
  • Knowledge of feature stores and model registries.