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Google Cloud Machine Learning Engineer Jobs in West Virginia

Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level ... Big Data and Machine Learning technologies * AI Tools (Claude, Cursor) * Automated testing ...

... engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning ... The Cloud Data Architect - Data Modeler ensures all solutions align with government CI/CD processes ...

WV

$200K/yr

About the role Coalition's machine learning models are only as good as the data they're trained on ... Partner with the data engineering team that builds and maintains the platform. * Cross-functional ...

$94K - $113K/yr

... and machine learning applications. Required Qualifications * Education: Bachelor's degree in ... Cloud Fundamentals: Working knowledge or project experience with AWS core services (S3, EC2, IAM ...

Senior Applied AI Engineer

Charleston, WV · Remote

$113K - $149K/yr

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software ... Familiarity with REST APIs, cloud-native applications, and distributed software systems. * Strong ...

Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with agile ... Passion for quality control and improving engineering practices. * Excellent communication and ...

New

Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with agile ... Passion for quality control and improving engineering practices. * Excellent communication and ...

Senior Software Engineer

Clarksburg, WV · On-site

$131K - $237K/yr

Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with agile ... Passion for quality control and improving engineering practices. * Excellent communication and ...

Implement and evolve systems that integrate with statistical models, and machine learning models to ... Practical experience deploying and running services in AWS or another major public cloud ...

Lead Data Engineer

WV · On-site +1

$103K - $123K/yr

... cloud-based solution to support all 204+ federal courts across the United States. GDIT is your ... AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO ...

Cloud Infrastructure Engineer

Charleston, WV · On-site

$99K - $130K/yr

Building pipelines to enable developers to successfully migrate to Cloud * Scripting ability in ... Share your passion for staying on top of tech trends, experimenting with and learning new ...

By harnessing the power of AI and machine learning, SailPoint automates and streamlines the ... Operating at the intersection of Solution Engineering,ProfessionalServicesand Product Management,a ...

New

Senior Data Engineer

WV · On-site +1

$95K - $129K/yr

... cloud-based solution to support all 204+ federal courts across the United States. GDIT is your ... AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO ...

Experience with cloud security across AWS, Azure, or Google Cloud. * Strong programming experience in Python or TypeScript. * Excellent communication and collaboration skills. * A mindset of both a ...

... machine learning models within enterprise data platforms. This position requires technical ... or Azure DevOps. * Foundational knowledge of enterprise virtualization, cloud architecture ...

Showing results 41-60

Google Cloud Machine Learning Engineer information

See West Virginia salary details

$18

$48

$67

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

As of Aug 23, 2026, the average hourly pay for google cloud machine learning engineer in West Virginia is $48.68, according to ZipRecruiter salary data. Most workers in this role earn between $41.49 and $55.48 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 West Virginia?

For Google Cloud Machine Learning Engineer jobs in West Virginia, the most frequently searched job titles are:

What job categories do people searching Google Cloud Machine Learning Engineer jobs in West Virginia look for?

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

What cities in West Virginia are hiring for Google Cloud Machine Learning Engineer jobs?

Cities in West Virginia with the most Google Cloud Machine Learning Engineer job openings:

Infographic showing various Google Cloud Machine Learning Engineer job openings in West Virginia as of June 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $101,263 per year, or $48.7 per hour.

Senior Staff Software Engineer

SailPoint

Charleston, WV

$113K - $149K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

This is a US-based remote role. You will be required to interview in person.

Due to FedRAMP requirements, must be a US citizen residing in the US.

About SailPoint
SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce, ensuring workers have the right access to do their job - no more, no less. Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time-matching the scale, velocity, and changing needs of today's cloud-oriented, modern enterprise.

About the role
As a Senior Staff Software Engineer at SailPoint, you will dive into a highly technical, fast-paced role where you drive engineering excellence and architectural direction. Your days will be spent designing, building, and deploying highly scalable, reliable microservices. You will write clean, robust Java code, build advanced prototypes to gather user feedback, and manage high-throughput data transformations. Additionally, you will integrate advanced AI tools such as Claude and Cursor into your daily workflow to accelerate high-quality software delivery.

About the team
The SailPoint Engineering Organization is a results-driven environment where high-quality professional engineering meets individual impact. Our team builds and maintains products on a mature, cloud-native event-driven microservices architecture hosted in AWS. We are passionate about developer autonomy, technical innovation, and delivering state-of-the-art SaaS platform solutions.

Roadmap for success

  • Day 30 (Onboarding & Integration): Successfully merge your first code to production. Map out the technical architecture of your primary domain and establish relationships with key engineering, product, and business stakeholders.

  • Day 60 (Ownership & AI Impact): Take full end-to-end ownership of a critical backend feature design. Author your first major architectural design document and implement an AI-assisted development workflow for your immediate team.

  • Day 90 (Delivery & Leadership): Successfully deploy your first major scalable system to production, meeting all observability and reliability metrics. Establish active mentorship with at least two mid/senior engineers and present a roadmap for technical simplification to leadership.

  • By 1 Year: Demonstrate significant participation and contributions to cross-team initiatives. Drive green field initiatives from the ground up while participating and leading virtual teams and managing dependencies. Participate in technical interview panels for new engineering candidates.

Responsibilities

  • Drive the design, implementation, and deployment of efficient, maintainable, robust micro-services to deliver medium-to-high complexity features.

  • Set a high bar for code/design reviews and fortify the team's coding/quality standards.

  • Collaborate with the technical teams, and product managers to implement features that meets our product vision

  • Work in an agile environment, collaborate with peers on designs, technical refinements, code reviews, testing and customer issues.

  • Continue to maintain the "We built it, we maintain it" SailPoint culture:Participate in the product OnCall and TechOps process.

  • Mentor junior members and guide them on technical solutions.

  • Managing development and release process of FedRAMP instances

  • Collaborate with peers on designs, code reviews, testing and UX/interactive designs

  • Develop automated tests across the full stack, complete with code-coverage metrics

  • Produce designs and rough estimates, and implement features based on product requirements.

  • Produce unit and end-to-end tests to improve code quality and maximize code coverage for new and existing features.

Requirements

  • 8+ years of professional software development experience

  • Strong Java experience

  • Experience in design/implementation of event-driven architectures and performant micro-services

  • Multi-tenant SaaS product development experience - server-side in Java & Go

  • Experience in designing, implementing RESTful APIs for an API-first application architecture

  • Great communication skills

  • BS in Computer Science, or a related field

  • Advanced experience with object-oriented analysis and design skills

  • Proven experience using AI tools (Claude, Cursor) to build releasable, maintainable code

  • Strong understanding of and experience with data pipelines and data transformations at scale

The Tech Stack

  • Java

  • AWS (Amazon Web Services)

  • Big Data and Machine Learning technologies

  • AI Tools (Claude, Cursor)

  • Automated testing frameworks

Preferred Skills

  • Experience with AWS

  • Experience with Continuous Delivery

  • Experience working on a Big Data/Machine Learning product

  • Experience instrumenting code for gathering production performance metrics

  • Education:Bachelors degree in Computer Science, Software Engineering, or a closely related technical field, or equivalent practical experience in large-scale software development.


Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint.


As a part of the total compensation package, this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission, along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect SailPoint's differing products, industries, and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary, for US-based employees, will be in this range from (min-max, USD):

$155,800 - $262,550.00

Base salaries for employees based in other locations are competitive for the employee's home location.

Benefits Overview

1. Health and wellness coverage: Medical, dental, and vision insurance

2. Disability coverage: Short-term and long-term disability

3. Life protection: Life insurance and Accidental Death & Dismemberment (AD&D)

4. Additional life coverage options: Supplemental life insurance for employees, spouses, and children

5. Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account

6. Financial security: 401(k) Savings and Investment Plan with company matching

7. Time off benefits: Flexible vacation policy

8. Holidays: 8 paid holidays annually

9. Sick leave

10. Parental support: Paid parental leave

11. Employee Assistance Program (EAP) and Care Counselors

12. Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options

13. Health Savings Account (HSA) with employer contribution

SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable law.

Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact applicationassistance@sailpoint.com or mail to 11120 Four Points Dr, Suite 100, Austin, TX 78726, to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.