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Mobile Machine Learning Jobs in Ohio (NOW HIRING)

... machine learning, mobile, etc.) * Ability to tackle design and functionality problems independently with little to no oversight * Practical cloud native experience * Experience in Computer Science ...

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... machine learning, mobile, etc.) • Ability to tackle design and functionality problems independently with little to no oversight • Practical cloud native experience - AWS, Azure • Ability to ...

Lead Cybersecurity Architect

Columbus, OH · On-site

$53.25 - $73.25/hr

... machine learning, mobile, etc.) • In-depth knowledge of the financial services industry or regulated industries • Practical cloud native experience • Deep knowledge of one or more software and ...

... machine learning, mobile, etc.) • Ability to tackle design and functionality problems independently with little to no oversight • Practical cloud native experience • Ability to evaluate current ...

... machine learning, mobile, etc.) • Preferred qualifications, capabilities, and skills If you find yourself suitable for this position, kindly send your updated resume and expected hourly rate to ...

Explore emerging tech-from artificial intelligence / machine learning to cloud-native engineering ... Life Insurance * 100% Company-Paid Mobile Phone Plan * 3 Weeks PTO + 7 Paid Holidays * Paid ...

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Mobile Machine Learning information

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How much do mobile machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for mobile machine learning in Ohio is $24.08, according to ZipRecruiter salary data. Most workers in this role earn between $13.70 and $19.18 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership responsibilities, specialized knowledge, and may be found in large tech companies or research institutions.

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.

Will MLE be replaced by AI?

Mobile Machine Learning Engineers (MLEs) develop and optimize machine learning models for mobile devices. While AI technologies continue to advance, MLEs focus on implementing efficient, lightweight models suitable for mobile hardware, and their role is expected to evolve rather than be fully replaced by AI itself. Skills in model optimization, deployment, and understanding mobile constraints remain essential for MLEs.

What engineer makes $500,000 a year?

Senior machine learning engineers, including those working on mobile applications, can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning and AI, and roles in high-paying industries or companies. Achieving this level often requires advanced degrees, specialized expertise, and leadership responsibilities.

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.

Which 3 jobs will survive AI?

Mobile Machine Learning professionals, data scientists, and AI system engineers are likely to continue thriving as AI advances, due to their expertise in developing, managing, and interpreting complex models. These roles require specialized skills in programming, statistics, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with AI tools and frameworks are essential for long-term job security in this field.

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 Ohio? The most popular types of Machine Learning jobs in Ohio are:
What cities in Ohio are hiring for Mobile Machine Learning jobs? Cities in Ohio with the most Mobile Machine Learning job openings:
Lead Software Engineer- Android

Lead Software Engineer- Android

JP Morgan Chase

Columbus, OH • On-site

Full-time

Medical, Retirement

Posted 12 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 491 frontline employees who took The Breakroom Quiz

58th of 149 rated banks


Job description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities:

  • Produces architecture and design artifacts for complex applications and ensures design constraints are met by software code development.
  • Proactively identifies hidden problems and patterns in data and uses these insights to improve coding hygiene and system architecture.
  • Contributes to software engineering communities of practice and participates in events that explore new and emerging technologies. 
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Adds to a team culture of diversity, opportunity, inclusion, and respect.
  • Focus on creating an informative, data-promoten journey with a customer-focused mindset
  • Demonstrate the ability to understand requirements and translate them into efficient code
  • Gain experience with Kotlin, Jetpack Compose, RxJava, LiveData, mobile UI fundamentals (from layout to animations), and RESTful API integration
  • Utilize experience with unit and functional testing libraries like Mockito and Espresso
  • Leverage experience with distributed systems, caching, and persistence solutions.
  • Apply understanding of architectural patterns such as MVP and MVVM, and application design patterns (Gang of Four).
  • Utilize understanding of build and CI systems such as Gradle and Jenkins

Required qualifications, capabilities, and skills:

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one or more programming language(s)
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
  • 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.)
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Practical cloud native experience
  • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Preferred qualifications, capabilities, and skills:

  • Work with mobile application team to setup monitoring and resolve production issues/crashes on mobile devices. Assist with troubleshooting, root cause analysis, and ensure that software bugs are corrected in an expedient manner. Communicate resolution & next steps.
  • Experience with mobile testing in areas like unit test, automation test, testing/debugging using emulator and device including experience with mobile application profiling for memory analysis, thread analysis and heap analysis on devices, emulators and simulators.
  • Can work with large codebases, managing shared resources and libraries and involvement in the ongoing development one or more mobile applications available in Apple's App Store or Google's Play Store.
  • Ability to troubleshoot and identify root causes under time pressure.
  • Experience building localized, multi-tenant solutions.
  • Strong experience with data structures and multithreading.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

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