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Mobile Machine Learning Jobs in Washington, DC (NOW HIRING)

Creating machine learning models that conduct text classification and topic modeling in Python ... Apply now with our easy 3-minute, mobile-friendly initial application process. Your future starts ...

Mobile Mechanic

Rockville, MD · On-site

$40/hr

Embarking on a career at RMA means embarking on continuous learning and growth. Whether you're ... Conduct inspections of diesel machinery and vehicles to detect signs of possible deterioration,

... mobile workforce and protecting AARP network, systems and data. A variety of technologies and practices are used including cloud computing, automation, artificial intelligence and machine learning ...

Showing results 41-60

Mobile Machine Learning information

See Washington, DC salary details

$13

$28

$135

How much do mobile machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for mobile machine learning in Washington, DC is $28.68, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $22.88 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 Washington, DC?

The most popular types of Machine Learning jobs in Washington, DC are:

What are popular job titles related to Mobile Machine Learning jobs in Washington, DC?

For Mobile Machine Learning jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Mobile Machine Learning jobs in Washington, DC look for?

The top searched job categories for Mobile Machine Learning jobs in Washington, DC are:

Senior Data Scientist - Wash DC; TS clearance required to apply

Washington, DC • On-site

$170K - $185K/yr

Full-time

Re-posted 24 days ago


Job description

Project Overview:This dynamic project supports the FBI in strengthening its mission-critical operations through the delivery of integrated technical, operational, and analytical services. The focus is on enhancing the FBI's enterprise systems by maintaining secure cloud environments such as AWS and Azure, while enabling advanced data capabilities through scalable ETL pipelines and the migration of custom-developed tools into enterprise platforms. In parallel, the team engages in forward-leaning research on emerging technologies including artificial intelligence, machine learning, IoT, and mobile messaging applications to inform next-generation solutions. As part of its operational mission, the project provides direct case support and real-time data analysis for high-profile events managed by the 24/7 operations center. Responsibilities:Plans and leads major technology assignments.Evaluates performance results and recommends major changes affecting short-term project growth and success.Functions as a technical expert across multiple project assignments.Collaborates with nontechnical, national security investigators and analysts to understand their data science needs, suggest solutions, and complete the work in a timely manner.Leads and/or design machine learning (ML), statistical analysis, and data analysis tasks.Leverages existing and/or conduct custom Extract Transform Load (ETL) work to aggregate data from multiple repositories and condition the data to provide novel insights.Interprets data, identify features and model variables, assess the quality of model outputs, generate alternatives, and conduct remediation.Finds and designs new approaches to handling, analyzing, and using large volumes of dataand/or data sets, and explore fundamental issues with data handling, search, and retention.Designs new software code to improve data search processes, and design, test, and validate the quality of data and data processes.Automates routine workflows and data analysis steps to assist with workflow automation.Reports results of analyses and provide actionable recommendations.Required Qualifications:Minimum Eight (8) years of relevant experience with a BS in Data Science, Mathematics, Information Science, Statistics, Engineering, Business Analytics, or related degree; OR Four (4) years of relevant experience with an MS degree in Data Science, Engineering, Mathematics, or related degree.Required Experience:Demonstrate high level of proficiency in all functional responsibilities and expert knowledge of data science and/or data analytics with: High proficiency in Python