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

Actalent

Software Perception Engineer

Dallas, TX · On-site

Working knowledge of mobile robotics perception for autonomy or advanced operator assist systems. * Working knowledge of computer vision, machine learning, and deep learning techniques applied to ...

New

WTS Paradigm LLC

Senior ML Ops Engineer

Irving, TX · On-site

$123K - $170K/yr

We are building the future with modern software engineering, agent-assisted systems, and mobile ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

Paradigm

Senior ML Ops Engineer

Irving, TX · Remote

$123K - $170K/yr

We are building the future with modern software engineering, agent-assisted systems, and mobile ... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ...

Adidev Technologies Inc

ML/AI Engineers

Dallas, TX · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a ...

Adidev Technologies Inc

ML/AI Engineers

Dallas, TX · On-site

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a ...

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

Mobile Machine Learning information

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How much do mobile machine learning jobs pay per hour?

As of Aug 4, 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

Senior Lead Software Engineer - Data / Machine Learning Operations

JPMorganChase

Plano, TX • On-site

Full-time

Re-posted 27 days ago

Job description

Job Summary:
JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions. As a Senior Lead Software Engineer, you will be part of an agile team that enhances and delivers technology products, focusing on building and deploying cloud-based solutions and driving significant business impact through your technical expertise.
Responsibilities:
• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Design and develop large-scale solutions or platforms using Cloud services (i.e. AWS) in alignment with the firm wide strategies and security controls
• Deploy and enable cloud based solutions at firm level, supporting complex analytics and day to day business operations
• Migrate legacy an big data applications at Cloud native applications with zero downtime
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Develop solutions or tools to monitor, provision components for automation or the processes, services, and reports
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Leverage your strong operational skills to develop impactful recommendations on upstream product, processes, or policy improvements that will optimize the user experience
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Adds to the team culture of diversity, opportunity, inclusion, and respect
Qualifications:
Required:
• Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Good knowledge of Machine Learning modelling as an engineer
• Advanced in one or more programming language(s) and framework(s) (i.e., Python, Java, Big Data, Data pipeline, Machine Learning, etc.)
• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Advanced knowledge of application, data, and infrastructure architecture disciplines
• Working experience in software development, OOPS and SDLC
• Ability to tackle design and functionality problems independently with little to no oversight
• Knowledge of the financial services industry and their TI systems
• Practical cloud native experience
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Preferred:
• AWS certifications (e.g. Solutions Architect Associate)
• Knowledge of RAG architectures and exposure to AI/Automation technologies that improve operations
• Experience with building Data Pipelines in Spark, Tuning Spark queries
• Understands Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)
• Working knowledge with Big Data platforms (i.e., Hadoop preferred)
• Experience in Cloud Technologies (i.e., AWS - Databricks preferred)
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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