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Google Cloud Machine Learning Engineer Jobs in Dallas, TX

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... Your expertise in big data technologies, cloud-based data platforms, and machine learning model ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team ... Drive performance optimization and scalability of ML systems across edge and cloud environments.

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform. GCP Professional Machine Learning Engineer certification is ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

... learning. • Experience with cloud platforms such as Google Cloud Platform (GCP), including ... Machine Learning Engineer certification is required. • Experience with version control systems ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Experience with cloud computing platforms such as AWS, Azure, or GCP. * Experience with version ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

... learning. • Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform. • GCP Professional Machine Learning Engineer ...

Deloitte

Cyber - Google Cloud Security - Manager

Dallas, TX

$109K - $148K/yr

... machine learning security, container security, data protection, monitoring, and secure delivery ... Serving as the primary day-to-day client contact, driving outcomes across engineering, security ...

MSR Cosmos

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

Google Cloud ML Engineer- Vertex AI & CCAI Chat Virtual Agent Expert Location: Dallas, TX (Day1 Onsite) Duration: Long Term We seek an experienced developer to design, build, and deploy advanced ...

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

As of Sep 7, 2026, the average hourly pay for google cloud machine learning engineer in Dallas, TX is $57.64, according to ZipRecruiter salary data. Most workers in this role earn between $49.13 and $65.67 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 the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Dallas, TX?

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

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The top searched job categories for Google Cloud Machine Learning Engineer jobs in Dallas, TX are:

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Cities near Dallas, TX 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 Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,449 per year, or $62.2 per hour.

Machine Learning Engineer II

7-Eleven

Irving, TX • On-site

Full-time

Posted 16 days ago

7-Eleven rating

4.3

Company rating: 4.3 out of 10

Based on 845 frontline employees who took The Breakroom Quiz

39th of 47 rated convenience stores

Job description

7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation - working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.
Job Summary
We are seeking a talented Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions that drive business value as part of our digital initiatives. As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your expertise in big data technologies, cloud-based data platforms, and machine learning model development, will contribute to the transformation of telemetry data and other large datasets into actionable insights.
Key Responsibilities:
  • Design, develop, test, and deploy machine learning models and data-driven solutions that transform store equipment telemetry data into actionable insights.
  • Work in enterprise environments to build and optimize scalable data pipelines using Python, PySpark, and Azure-based technologies.
  • Process, analyze, and manipulate large structured and unstructured datasets to support analytics and machine learning initiatives.
  • Collaborate with data engineers, data scientists, product owners, and business stakeholders to translate business requirements into technical solutions.
  • Develop, evaluate, and tune machine learning models using appropriate algorithms and statistical techniques.
  • Implement MLOps best practices for model deployment, monitoring, and lifecycle management.
  • Create visualizations, dashboards, and presentations to communicate insights and recommendations to technical and non-technical audiences.
  • Participate in code reviews, technical design discussions, and continuous improvement initiatives.

Required Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • 5+ years of experience delivering big data and machine learning solutions in enterprise environments.
  • Strong programming experience in Python and PySpark.
  • Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps.
  • Experience building, training, validating, and deploying machine learning models.
  • Solid understanding of data structures, algorithms, software engineering principles, and distributed computing concepts.
  • Experience working with large-scale datasets and cloud-native architectures.
  • Strong analytical, problem-solving, and communication skills.

Preferred Qualifications:
  • Experience deploying and operationalizing machine learning models in Azure Databricks.
  • Experience with MLOps frameworks and CI/CD pipelines for machine learning workloads.
  • Experience with data visualization tools such as Power BI, Tableau, or equivalent platforms.
  • Experience working with equipment telemetry data or on equipment maintenance projects.
  • Knowledge of containerization technologies and cloud-native application development.

Machine Learning Expertise:
  • Clustering and segmentation techniques.
  • Generalized Linear Models (GLM), Linear Regression, and Logistic Regression.
  • Decision Trees and Random Forests.
  • Gradient boosting techniques including XGBoost.
  • K-Nearest Neighbors (KNN).
  • Support Vector Machines (SVM).
  • Artificial Neural Networks (ANN) and deep learning concepts.
  • Model evaluation, feature engineering, hyperparameter tuning, and performance optimization.

Success Factors:
  • Ability to work effectively in a fast-paced, collaborative environment.
  • Strong ownership mindset and commitment to delivering high-quality solutions.
  • Ability to communicate complex technical concepts to diverse stakeholder groups.
  • Passion for continuous learning and innovation in machine learning and cloud technologies.

If an hourly or salary range is included in this ad it represents the range 7-Eleven in good faith believes is the range of compensation for this role at the time of this posting. The Company may ultimately pay more or less than the posted range. This range is only applicable for jobs to be performed in this state. This range may be modified in the future. No amount is considered to be wages or compensation until such amount is earned, vested, and determinable under the terms and conditions of the applicable policies and plans. The amount and availability of any bonus, commission, long-term incentive compensation, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.
For a general description of all benefits 7-Eleven is offering in the US for the position, please visit this link.
For a general description of all benefits 7-Eleven is offering in Canada for the position, please visit this link.

What 7-Eleven employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About 7-Eleven

Sourced by ZipRecruiter

As the world’s first convenience store, our top priority has always been to give customers the most convenient experience possible to consistently meet their needs. 7-Eleven aims to be a one-stop shop for consumers – a place people can always rely on to deliver what they want, when, where, and how they want it.

Industry

Food services and drinking places

Company size

10,000+ Employees

Headquarters location

Dallas, TX, US

Year founded

1927

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