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Quantum Machine Learning Engineer Jobs in Fort Worth, TX

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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 ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

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 ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Yum Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

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-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

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All JobsQuantum Machine Learning Engineer JobsQuantum Machine Learning Engineer Jobs in Fort Worth, TX

Quantum Machine Learning Engineer information

See Fort Worth, TX salary details

$30.2K

$123.4K

$185.4K

How much do quantum machine learning engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for quantum machine learning engineer in Fort Worth, TX is $123,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,300.00 and $148,600.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

What are the key skills and qualifications needed to thrive as a quantum machine learning engineer?

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

What are popular job titles related to Quantum Machine Learning Engineer jobs in Fort Worth, TX?

For Quantum Machine Learning Engineer jobs in Fort Worth, TX, the most frequently searched job titles are:

What job categories do people searching Quantum Machine Learning Engineer jobs in Fort Worth, TX look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Fort Worth, TX are:

What cities near Fort Worth, TX are hiring for Quantum Machine Learning Engineer jobs?

Cities near Fort Worth, TX with the most Quantum Machine Learning Engineer job openings:

Quantum Machine Learning Engineer jobs near you
Infographic showing various Quantum Machine Learning Engineer job openings in Fort Worth, TX as of June 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $123,291 per year, or $59.3 per hour.

Machine Learning Engineer

Rivago infotech inc

Dallas, TX • On-site

Other

Posted 2 days ago

New

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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