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Google Cloud Machine Learning Engineer Jobs in Dallas, TX

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 ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Cloud data warehouse platform using the Snowpark framework Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and ...

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Yum! Brands

Machine Learning Engineer II

Plano, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

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 ...

Danta Technologies

Gen AI Engineer

Irving, TX · On-site

  • Medical

  • Dental

  • Vision

Proven experience in AI, Machine Learning, and Deep ... Learning. * Strong proficiency in Python, PySpark, and PyTorch. * Experience with Google Cloud ...

Tiger Analytics Inc.

Machine Learning Engineer

Plano, TX · On-site

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join ... Strong understanding of cloud-native applications , container orchestration (ECS, Docker) , and AWS ...

Tiger Analytics Inc.

Machine Learning Engineer

Plano, TX · On-site

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join ... Strong understanding of cloud-native applications , container orchestration (ECS, Docker) , and AWS ...

Tiger Analytics

Machine Learning Engineer

Plano, TX · On-site

$120 - $150/hr

Overview Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI ... Strong understanding of cloud-native applications , container orchestration (ECS, Docker) , and AWS ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Dallas, TX

Google Cloud Machine Learning Engineer information

See Dallas, TX salary details

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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 Dallas, TX is $62.24, according to ZipRecruiter salary data. Most workers in this role earn between $53.03 and $70.91 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 Dallas, TX?

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

What job categories do people searching Google Cloud Machine Learning Engineer jobs in Dallas, TX look for?

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

What cities near Dallas, TX are hiring for Google Cloud Machine Learning Engineer jobs?

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.

GCP Data Engineer with AI/ML Integration & MLOps

Tror AI for everyone

Irving, TX • On-site

Contractor

Re-posted 8 days ago

Job description

Role : GCP Data Engineer with AI/ML Integration & MLOps

Location : Irving, Texas 75039  (100% onsite)

Hire type : Contract

Interview Mode : 1 Video interview and client interview will be In person 

Overview

We are seeking a GCP Data Engineer with deep, hands-on architectural and development

experience in Google Cloud Platform’s big data ecosystem. You will be responsible for

designing, building, and optimizing a modern data lakehouse architecture. Your primary focus

will be leveraging BigLake, BigQuery, Google Cloud Storage (GCS), and Vertex AI to create

seamless, scalable data pipelines and machine learning integrations that drive business

intelligence and predictive analytics.

Key Responsibilities

  • Lakehouse Architecture & Development:
  • Architect and maintain a scalable data lakehouse using Google Cloud Storage
  • (GCS) as the foundational data lake and BigLake to unify data warehouses and data lakes.
  • Implement fine-grained security (row-level and column-level access controls) and
  • data governance across open file formats (Parquet, Iceberg, ORC) using BigLake.
  • Data Warehousing & Optimization:
  • Design and manage complex, highly scalable data models within Big Query.
  • Perform deep performance tuning and cost optimization of Big Query jobs utilizing
  • clustering, partitioning, materialized views, and slot capacity management.

AI/ML Integration & MLOps:

  • Collaborate with Data Scientists to operationalize machine learning models using
  • Vertex AI.
  • Build robust data pipelines to feed Vertex AI Feature Store, manage model
  • training workflows and deploy ML models into production.
  • Utilize Big Query ML (BQML) for in-database predictive modeling and analytics
  • where appropriate.

Data Pipeline Engineering:

  • Design, develop, and orchestrate batch and streaming data pipelines (using tools
  • like Dataflow, Dataproc, or Cloud Composer/Airflow) to ingest data from diverse
  • sources into GCS and BigQuery.
  • Data Governance & Best Practices:
  • Establish data lifecycle management policies in GCS.
  • Ensure data quality, reliability, and security compliance across the entire GCP big
  • data stack.
  • Mentor junior engineers and lead code/architecture reviews.

Required Qualifications

  • Experience: 5+ years of dedicated Data Engineering experience, with at least 3+ years
  • focused exclusively on the Google Cloud Platform (GCP).

Deep GCP Big Data Expertise:

  • BigQuery: Expert-level knowledge of BigQuery architecture, advanced SQL,
  • analytical functions, query profiling, and optimization techniques.
  • BigLake: Proven experience utilizing BigLake for multi-cloud or lakehouse
  • architectures, managing open-source formats (e.g., Apache Iceberg/Parquet),
  • and enforcing unified security policies.
  • GCS: Deep understanding of GCS storage classes, object lifecycle management,
  • and optimizing GCS for big data workloads.
  • Vertex AI: Hands-on experience with Vertex AI pipelines, endpoints, feature
  • stores, or deploying ML models into scalable data environments.
  • Programming Skills: Advanced proficiency in Python and SQL. Familiarity with Java,
  • Scala, or Go is a plus.
  • Data Orchestration & CI/CD: Experience with orchestration tools (e.g., Apache Airflow,
  • Cloud Composer) and modern CI/CD pipelines (e.g., GitHub Actions, Terraform, Cloud
  • Build).

Preferred/Bonus Qualifications

  • GCP Certifications: Google Cloud Certified - Professional Data Engineer or
  • Professional Machine Learning Engineer.