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Machining Engineer Jobs in Texas (NOW HIRING)

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 ...

As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Samsung's deployed network elements.

New

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 ...

Machine Learning Engineer

Frisco, TX ยท 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 ...

Senior Machining Process Engineer

San Antonio, TX ยท On-site

$87K - $113K/yr

The Senior Machining Process Engineer provides technical and production support, process development, and optimization across Aerospace and Industrial gas turbine programs. This role spans NPI ...

Senior Machining Process Engineer

San Antonio, TX ยท On-site

$87K - $113K/yr

The Senior Machining Process Engineer provides technical and production support, process development, and optimization across Aerospace and Industrial gas turbine programs. This role spans NPI ...

Knowledge of programmable logic controllers (PLCs), tooling setup, materials handling, and basic math skills for machining calculations * Warehouse experience or familiarity with factory safety ...

Showing results 21-40

Machining Engineer information

See Texas salary details

$61.5K

$84.6K

$119.7K

How much do machining engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for machining engineer in Texas is $84,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,100.00 and $90,400.00 per year, depending on experience, location, and employer.

What are some common challenges machining engineers face when optimizing manufacturing processes?

Machining Engineers frequently encounter challenges such as minimizing cycle times while maintaining product quality, troubleshooting equipment issues, and ensuring efficient use of materials. They must balance tight production deadlines with the need for precision and adherence to safety standards. Collaboration with operators, design engineers, and quality control teams is essential to identify process improvements and implement new technologies. Adapting to rapidly advancing manufacturing technologies and integrating automation can also present ongoing learning opportunities and challenges.

What is a machining engineer?

Machining Engineers are professionals who design, develop, and optimize processes for manufacturing parts using machining methods such as milling, turning, drilling, and grinding. They work with a variety of materials and oversee the programming, setup, and operation of machine tools, often using computer-aided manufacturing (CAM) software. Their main goal is to ensure products are manufactured efficiently, accurately, and cost-effectively, while maintaining quality and safety standards. Machining Engineers often collaborate with design, production, and quality teams to improve processes and troubleshoot issues in the manufacturing environment.

What is the difference between Machining Engineer vs Manufacturing Engineer?

AspectMachining EngineerManufacturing Engineer
CredentialsTypically requires a degree in mechanical or manufacturing engineering, with certifications in CAD/CAM softwareSimilar credentials, often with additional focus on production processes and quality management
Work EnvironmentWorks primarily in machine shops, CNC facilities, or manufacturing plants focusing on machining processesWorks across entire production lines, including process planning, quality control, and equipment optimization
Industry UsageCommonly employed in industries with heavy machining needs like aerospace, automotive, and toolingUsed broadly in manufacturing sectors including electronics, consumer goods, and industrial equipment

While both roles require engineering knowledge and involve manufacturing processes, Machining Engineers focus specifically on machining operations and CNC programming, whereas Manufacturing Engineers oversee entire production systems. The choice depends on whether you prefer specialized machining work or broader manufacturing process management.

What are the key skills and qualifications needed to thrive as a machining engineer?

To thrive as a Machining Engineer, you need a solid background in mechanical engineering, manufacturing processes, and materials science, often supported by a bachelor's degree in engineering. Proficiency with CAD/CAM software, CNC programming, and knowledge of quality control systems are typically required. Strong problem-solving abilities, attention to detail, and effective communication set outstanding professionals apart in this role. These skills are crucial for optimizing machining operations, ensuring product quality, and driving continuous process improvement in manufacturing environments.

What job categories do people searching Machining Engineer jobs in Texas look for?

The top searched job categories for Machining Engineer jobs in Texas are:

Infographic showing various Machining Engineer job openings in Texas as of August 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $84,605 per year, or $40.7 per hour.

Machine Learning Engineer

Rivago infotech inc

Dallas, TX โ€ข 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.