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Google Cloud Machine Learning Engineer Jobs in Indiana

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 ...

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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 Aug 18, 2026, the average hourly pay for google cloud machine learning engineer in Indiana is $59.84, according to ZipRecruiter salary data. Most workers in this role earn between $51.01 and $68.17 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.

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The top searched job categories for Google Cloud Machine Learning Engineer jobs in Indiana are:

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Google Cloud Machine Learning Engineer jobs near you

Senior Cloud Networking Engineer

Purdue University

West Lafayette, IN • On-site

$53.50 - $71.75/hr

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Purdue University rating

7.5

Company rating: 7.5 out of 10

Based on 136 frontline employees who took The Breakroom Quiz

312th of 618 rated colleges and universities

Job description

Senior Cloud Networking Engineer
City: West Lafayette
Job Description:
Job Summary
Senior Cloud Network Engineer
Purdue University - West Lafayette, Indiana
Purdue IT is seeking a Senior Cloud Network Engineer to help shape the future of our cloud ecosystem. This role offers a unique opportunity to contribute to a growing multi-cloud environment while partnering with campus and IT leaders to turn strategy into secure, scalable solutions that support teaching, learning, and research.
What You'll Do
  • Contribute to the design and evolution of Purdue's multi-cloud networking strategy across AWS, Azure, and Google Cloud Platform
  • Collaborate with IT and campus leadership to translate strategic goals into practical, reliable cloud network solutions
  • Design and improve virtual network architecture to support seamless workload mobility across environments
  • Evaluate, implement, and maintain tools for monitoring cloud performance, usage, cost, and system health
  • Support secure, resilient, and efficient cloud operations aligned with institutional priorities

Why This Role Stands Out
  • Impactful work: Play a meaningful role in advancing enterprise cloud capabilities at a leading research institution
  • Strategic influence: Help shape cloud direction-not just execute within it
  • Technical depth: Work across hybrid and multi-cloud networking environments with evolving technologies
  • Collaborative environment: Partner with skilled professionals across IT and academic units

What You Bring
  • Experience designing and supporting cloud networking in one or more major platforms (AWS, Azure, Google Cloud Platform)
  • Strength in hybrid connectivity and integrating cloud with on-prem infrastructure
  • Ability to balance long-term strategy with practical implementation
  • Curiosity and adaptability in a rapidly changing technical landscape

What We're Looking For
Education and Experience Required:
  • Bachelor's degree in networking, engineering, cloud technologies, AI (Artificial Intelligence) or related field
  • Four (4) years of experience in cloud services including architecture design, supporting, and deploying solutions for cloud engineering, including AWS, Google Cloud Platform, Azure, or other cloud technologies, including cloud networking and hybrid connectivity, design of secure virtual networks, high-throughput research data paths, and connectivity between on-premises systems, cloud platforms, and AI research hubs
  • An equivalent combination of education and experience may be considered

Preferred:
  • Multi-cloud engineering experience, with the ability to integrate and interoperate Google Cloud Platform services alongside existing AWS and Azure environments to support diverse academic and administrative workloads
  • Experience supporting AI research platforms and tools, including managed AI services, model experimentation environments, and emerging multi-agent systems (such as trusted-tester or early-access AI tools)

Skills Required:
  • Ability to:
    • travel to remote campuses (5%) and work closely with network engineering staff with on-prem network integrations if needed
    • help define and operationalize institutional cloud and AI strategy, translating executive-level vision into scalable technical architectures and services Strong stakeholder engagement skills, working with faculty, researchers, IT leadership, and external partners (such as Google Public Sector) to implement shared goals
  • Excellent verbal and written communication skills

Additional Information:
  • Purdue University will not sponsor employment authorization for this position
  • A background check will be required for employment in this position
  • FLSA: Exempt (Not Eligible for Overtime)
  • Retirement Eligibility: Defined Contribution Waiting Period
  • Benefit Statement: Purdue University offers a substantial Benefit Package including medical, dental, and vision insurance as well as a generous paid time off package for sick and vacation days

Career Stream
Professional 3
  • Pay Band S075
  • Job Code #20003622

Career path maker: ;br>
Who We Are
Purdue is a community built on collaboration, with global perspectives, Boilermaker pride and endless opportunity to live, learn and grow. Join us and contribute to our culture.
Equal Opportunity Employer
Purdue University is an EOE employer.

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