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Freelance Google Machine Learning Engineer Jobs in Texas

Rivago infotech inc

Machine Learning Engineer

Dallas, TX · On-site

Machine Learning Engineer - Fraud Detection Location: Dallas, TX (100% Onsite) Role Summary We are ... Google Cloud Platform and Databricks * Neo4j / Graph Databases and Feature Stores * Data Pipelines ...

Cymertek Corporation

Machine Learning Engineer

San Antonio, TX · On-site

$110 - $150/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Q2 India

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

  • Medical

Machine Learning Engineer page is loaded## Machine Learning Engineerlocations: Austin, TXtime type: Full timeposted on: Posted Yesterdayjob requisition id: REQ-12438# **As passionate about our people ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and ...

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard ... Proficiency with Microsoft Office 365, Google Workspace, and Adobe Acrobat. * Occasional domestic ...

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $130K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

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Freelance Google Machine Learning Engineer information

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Texas?

The most popular types of Google Machine Learning Engineer jobs in Texas are:

What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Texas?

For Freelance Google Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Freelance Google Machine Learning Engineer jobs in Texas look for?

The top searched job categories for Freelance Google Machine Learning Engineer jobs in Texas are:

What cities in Texas are hiring for Freelance Google Machine Learning Engineer jobs?

Cities in Texas with the most Freelance Google Machine Learning Engineer job openings:

Freelance Google Machine Learning Engineer jobs near you
Infographic showing various Freelance Google Machine Learning Engineer job openings in Texas as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer

Rivago infotech inc

Dallas, TX • On-site

Other

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

Job description

Role: Machine Learning Engineer - Fraud Detection

Location: Dallas, TX (100% Onsite)

 

Role Summary

We are looking for a Machine Learning Engineer to build and support production-grade fraud detection solutions. The role focuses on real-time inference, feature engineering, APIs, graph-based fraud detection, and production deployment support.

 

Key Skills

  • Machine Learning Engineering and Real-Time Inference
  • Python, APIs, and Microservices
  • Google Cloud Platform and Databricks
  • Neo4j / Graph Databases and Feature Stores
  • Data Pipelines and Feature Engineering
  • MLOps, Monitoring, and Production Support
  • Agentic AI Architecture (good to have)

 

Responsibilities

  • Build and deploy fraud detection services for production use.
  • Develop low-latency inference solutions with a target of less than 250 ms.
  • Design feature engineering pipelines for ML use cases.
  • Integrate ML models with REST APIs and microservices.
  • Support graph-based fraud detection using Neo4j.
  • Improve scoring performance, reliability, and scalability.
  • Work with MLOps teams for releases, monitoring, and production support.
  • Support data quality, governance, and operational activities.

 

Required Qualifications

  • Hands-on experience in Python and ML model deployment.
  • Experience with APIs, microservices, and production ML systems.
  • Knowledge of data pipelines, data engineering, and feature stores.
  • Exposure to Google Cloud Platform, Databricks, Data Lake, or Data Warehouse platforms.
  • Basic understanding of MLOps, monitoring, and release support.
  • Good communication and problem-solving skills.

 

Nice to Have

  • Fraud detection, risk analytics, or scoring model experience.
  • Experience with Neo4j or graph-based ML solutions.
  • Understanding of Agentic AI architecture.

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