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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 ...

Deloitte

Oracle Gen AI Manager

Dallas, TX · On-site

... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ... Do you have the ability to transform an organization through the latest social, mobile, and ...

Genpact

M365 Copilot Software Engineer

Dallas, TX · Hybrid

... and Azure Machine Learning into production solutions building agentic and generative AI ... Partner with middleware and mobile engineers to define clean API protocols using M365 and Azure as ...

Ampcus Inc

Mainframe Engineer

Plano, TX · On-site

$47.25 - $60.75/hr

... machine learning, mobile, etc.). • Knowledge in scheduling tool CA-7. • Knowledge of version and revision control practices and procedures, using Endeavor. Preferred : • Knowledge in Mainframe ...

GM Financial

SDE I- Adobe Exp Platform

Irving, TX · On-site

We're committed to AI-powered transformation, using advanced machine learning and automation to ... You'll collaborate with experienced engineers to develop real-world applications across web, mobile ...

GM Financial

Software Development Engineer II

Arlington, TX · On-site

$85K - $117K/yr

We're committed to AI-powered transformation, using advanced machine learning and automation to ... Develop product features for any or all of the following: data marketplaces, mobile applications ...

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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 Aug 11, 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 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 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 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 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 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

Business Strategy, Analytics

Samsung Electronics America

Plano, TX • On-site

Full-time

Re-posted 24 days ago

Samsung Electronics rating

6.7

Company rating: 6.7 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

125th of 156 rated electronics manufacturers

Job description

Job Summary:
Samsung Electronics America, Inc. (SEA) is a leader in mobile technologies and consumer electronics. The Business Strategy, Analytics role focuses on developing and executing business strategy analytics, collaborating with cross-functional teams to analyze market trends and drive strategic initiatives to achieve business objectives.
Responsibilities:
• Analyze market trends, consumer behavior, and competitive activities to identify growth opportunities and inform go-to-market strategies.
• Conduct sales analysis to evaluate product and sales channel performance, identifying areas for improvement and innovation.
• Collaborate with strategy, sales, and operations teams to prepare comprehensive reports and presentations that communicate insights and recommendations to senior leadership.
• Monitor industry developments and emerging technologies to assess their potential impact on business strategy.
• Lead ad-hoc projects and initiatives as needed to address strategic challenges and opportunities.
Qualifications:
Required:
• Bachelor's degree in business administration, economics, statistics, or a related field; MBA or advanced degree preferred.
• 6-8 years of experience in analytics or related fields, with a focus on business strategy or operations.
• Strong analytical skills with proficiency in data analysis tools (e.g., Excel, SQL, Tableau).
• Experience with market research methodologies and sales performance evaluation.
• Strong communication and presentation abilities, capable of influencing stakeholders at all organizational levels.
Preferred:
• Experience in the consumer electronics or retail industry.
• Knowledge of advanced analytics techniques such as predictive modeling and machine learning.
• Prior experience with 3rd party data sources such as NPD, IDC, Nielsen, Strategy Analytics, or Canalys.
Company:
Samsung Electronics America engages in high-tech electronics manufacturing and digital media. Founded in 1978, the company is headquartered in Ridgefield Park, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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