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Mobile Machine Learning Jobs in Irving, TX (NOW HIRING)

Hirekeyz Inc

Mainframe IMS DB Developer

Plano, TX · On-site

$47 - $60.25/hr

Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) * Experience using DevOps ...

JPMorgan Chase & Co.

AI Lead Security Engineer

Plano, TX · On-site

$120 - $160/hr

... machine learning, mobile, etc.) * Extensive experience with threat modeling, discovery, vulnerability, and penetration testingc * Ability to tackle design and functionality problems independently ...

Apex Informatics

AWS Data Engineer

Plano, TX · On-site

$109K - $131K/yr

... intelligence, machine learning, mobile, etc.) • Proficiency in automation and continuous delivery methods. • Proficient in all aspects of the Software Development Life Cycle. • Solid ...

Virtusa Corporation

Senior Consultant

Plano, TX · On-site

Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). Core Java (version 17 or ...

JPMorgan Chase & Co.

Product Security Architect

Plano, TX · On-site

$180 - $280/hr

Applies experience with artificial intelligence, machine learning, or mobile technologies. * Applies hands‑on cloud experience with AWS, Google Cloud, or Azure. * Exhibits expertise in web and ...

JPMorgan Chase & Co.

Lead Software Engineer

Plano, TX · On-site

$137K - $185K/yr

Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications ...

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All JobsMobile Machine Learning JobsMobile Machine Learning Jobs in Irving, TX

Mobile Machine Learning information

See Irving, TX salary details

$11

$24

$114

How much do mobile machine learning jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for mobile machine learning in Irving, TX is $24.32, according to ZipRecruiter salary data. Most workers in this role earn between $13.85 and $19.38 per hour, depending on experience, location, and employer.

What is mobile machine learning?

Mobile machine learning refers to the development and deployment of machine learning models on mobile devices such as smartphones and tablets. It enables apps to perform tasks like image recognition, language translation, and speech processing directly on the device without needing to send data to the cloud. This approach improves privacy, reduces latency, and can work even without an internet connection. Developers use frameworks like TensorFlow Lite, Core ML, and PyTorch Mobile to optimize models for the limited resources of mobile hardware.

What are some common challenges faced by mobile machine learning engineers when deploying models on mobile devices?

Mobile Machine Learning engineers often encounter challenges related to limited computational resources and memory constraints on mobile devices. Optimizing models for efficient inference without significant loss in accuracy is a key hurdle, as is ensuring compatibility across different devices and operating systems. Additionally, balancing power consumption and real-time performance is critical, so engineers frequently collaborate with mobile app developers and hardware specialists to deliver seamless user experiences while maintaining model integrity.

What are the key skills and qualifications needed to thrive as a mobile machine learning engineer, and why are they important?

To thrive as a Mobile Machine Learning Engineer, you need a solid background in computer science, machine learning, and mobile application development, often supported by a relevant degree and experience. Proficiency with ML frameworks (like TensorFlow Lite or Core ML), mobile platforms (Android/iOS), and deployment tools is typically required. Strong problem-solving skills, adaptability, and effective communication set standout professionals apart in this field. These skills are crucial for successfully developing, optimizing, and integrating machine learning models into efficient and user-friendly mobile applications.

What is the difference between Mobile Machine Learning vs Data Scientist?

AspectMobile Machine LearningData Scientist
Required CredentialsBachelor's in CS, ML, or related; experience with mobile platformsBachelor's or higher in CS, Statistics, or related; data analysis skills
Work EnvironmentMobile app development teams, on-device processingData analysis teams, research environments
Industry UsageMobile app companies, tech startupsFinance, healthcare, tech firms
Common Search/ComparisonYesYes

Mobile Machine Learning focuses on developing ML models optimized for mobile devices and integrating them into mobile apps. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming and ML knowledge, Mobile Machine Learning emphasizes on-device deployment and mobile platform expertise, whereas Data Scientists focus on data analysis and model development for broader applications.

What are the most commonly searched types of Machine Learning jobs in Irving, TX?

The most popular types of Machine Learning jobs in Irving, TX are:

What are popular job titles related to Mobile Machine Learning jobs in Irving, TX?

For Mobile Machine Learning jobs in Irving, TX, the most frequently searched job titles are:

What job categories do people searching Mobile Machine Learning jobs in Irving, TX look for?

The top searched job categories for Mobile Machine Learning jobs in Irving, TX are:

What cities near Irving, TX are hiring for Mobile Machine Learning jobs?

Cities near Irving, TX with the most Mobile Machine Learning job openings:

Mobile Machine Learning jobs near you

Mainframe IMS DB Developer

Hirekeyz Inc

Plano, TX • On-site

$47 - $60.25/hr

Full-time

Re-posted 29 days ago

Job description

Job Title: Mainframe IMS DB Developer 

Location: Plano, TX and Wilmington, DE – 5 days onsite

Job Type: Contract/W-2/Full Time

Long Term Project

Job Responsibilities:

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems

Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems

Produces design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Contributes to software engineering communities of practice and events that explore new and emerging technologies

Adds to team culture of diversity, equity, inclusion, and respect
Required Qualifications, Capabilities, And Skills

  • Formal training or certification on software engineering concepts and 3+ years of applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Hands-on experience in Mainframe Assembler programming, IMS, DB2
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Overall knowledge of the Software Development Life Cycle
  • Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Experience using DevOps tools in a cloud environment, such as Ansible, Docker, GitHub, Jenkins, Kubernetes and SonarQube
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages

Preferred Qualifications, Capabilities, And Skills:

  • Exposure to cloud technologies
  • Familiarity with Logging, Observability and Monitoring tools