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Google Cloud Machine Learning Engineer Jobs in Remote, OR

Atos

Head of AI

OR · On-site +1

Foster a culture of engineering rigor, responsible AI, collaboration, and continuous learning ... Cloud: AWS, Microsoft Azure, Google Cloud Platform * AI/ML: Agentic AI, Python, PyTorch/TensorFlow ...

Atos

Head of AI

OR · On-site +1

Foster a culture of engineering rigor, responsible AI, collaboration, and continuous learning. • ... Cloud: AWS, Microsoft Azure, Google Cloud Platform * AI/ML: Agentic AI, Python, PyTorch/TensorFlow ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Remote, OR

Google Cloud Machine Learning Engineer information

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

As of Jul 2, 2026, the average hourly pay for google cloud machine learning engineer in Remote, OR is $62.82, according to ZipRecruiter salary data. Most workers in this role earn between $53.56 and $71.59 per hour, depending on experience, location, and employer.

What are Google Cloud Machine Learning Engineers?

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, and why are they important?

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 Remote, OR? For Google Cloud Machine Learning Engineer jobs in Remote, OR, the most frequently searched job titles are:
What job categories do people searching Google Cloud Machine Learning Engineer jobs in Remote, OR look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Remote, OR are:
Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Google Cloud Machine Learning Engineer job openings in Remote, OR as of June 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $130,673 per year, or $62.8 per hour.

Account Executive- Northeast

Venice Security LTD

Myrtle Point, OR • Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

Be an early applicant

Job description

Company Overview

Come join Venice, the company redefining Privileged Access Management (PAM) for the AI era. While legacy players are costly, clunky, and stuck in the past, Venice provides dynamic, AI-aware privilege management that secures human, machine, and AI identities agentlessly.

Venice is already selling to the biggest enterprise in the world, with a product already displacing incumbents in Fortune 200 enterprises. We are looking for a founding-level AE to join our GTM team and turn our massive inbound momentum into scaled revenue.

Summary

In this role, you will be the first boots on the ground for the Northeast You will report to SVP Sales, and work closely with our founding team. This isn't a "sit back and wait for leads" role. Because we are early, we need an AE who is obsessed with meeting targets and isn't afraid to get their hands dirty. You will own the full cycle: from aggressive prospecting and pipe generation to closing six-figure enterprise deals.

What You’ll Do

  • Build the Region from Scratch: Develop and execute a territory plan to hunt and close new business across New England.
  • Own the Full Cycle: Manage the entire sales process from initial cold outreach and qualifying to technical demos (partnering with SEs) and final contract negotiation.
  • Displace Legacy Giants: Confidently position Venice against legacy PAM providers, demonstrating how we reduce standing privileges by 95% in weeks, not years.
  • Execute with Velocity: Drive a high-activity sales motion to convert our existing pipeline.
  • Shape the Playbook: As a founding AE, you will provide direct feedback to Product and Marketing, helping us build the GTM DNA of the company.
  • Forecast Accurately: Maintain expert-level hygiene in Salesforce, providing predictable visibility into your territory’s growth.

Why Join Us?

  • Founding Impact: You are the first GTM hire in this region. You aren't just a number; you are shaping the company's future.
  • Unrivaled Product: We are seeing 24x faster onboarding than our competitors. When you demo Venice, it actually works.
  • Career Upside: Meaningful early-stage equity and a clear path to leadership as we scale toward Series B.
  • Comprehensive Benefits: Competitive base + uncapped commissions, PPO Health Plan, dental,vision, ST/LT disability, Up to 4% match to your 401K, flexible PTO, and home office stipend.

Requirements:
  • The "Hunter" Mentality: 6+ years of SaaS sales experience, with at least 3 years in Enterprise Cybersecurity (IAM, PAM, SSE, or Cloud Security preferred).
  • Early-Stage Grit: Experience in a hyper-growth environment where you had to build your own pipeline and navigate ambiguity.
  • Proven Closing Power: A track record of consistently hitting or exceeding $1M+ annual quotas and closing six-figure deals.
  • Technical Literacy: Ability to hold your own in a room with CISOs and security engineers, explaining the value and ROI that is unique to our technology.
  • Methodology Mastery: Formal training in MEDDICCC or Command of the Message is highly preferred.
  • Location: Must be based in the territory (Northeast) to facilitate regular travel for face-to-face customer meetings.