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Mobile Machine Learning Jobs in Florida (NOW HIRING)

Altamira Technologies Corp.

Data Scientist

Tampa, FL · On-site

... and machine learning techniques. This postion requires 25% travel supporting the Mobile Training team. Experience: * Interpret and analyze data using exploratory mathematics and statistical ...

USM

Data Scientist-----Need GC and USC

Orlando, FL · On-site

... e-commerce, Social , Mobile, Cloud, Analytics (SMAC) and DevOps. USM, a US ensured Minority ... Uses descriptive and inferential statistics, data mining, predictive modeling and machine learning ...

University of Miami

Post Doctoral Associate

Coral Gables, FL

$46K - $63K/yr

... machine learning. * Design and conduct experimental studies involving robotic platforms such as dual-arm manipulators, mobile robots, and wearable/exoskeleton robotic systems. * Present research at ...

KeyMe

Mobile Operations Technician (Car Keys)

Miami, FL · On-site

$40K - $60K/yr

Van & Equipment Maintenance: Assist with daily van setup and maintain tools, machines, and ... Comfortable working with your hands, using tablets/mobile apps, and learning new technical skills.

BidMachine

Lead In‑House Legal Counsel

Parkland, FL · On-site

Mobile advertising identifiers * Attribution technologies * Consent management frameworks * AI and machine learning use cases involving advertising data * Support implementation and governance of ...

BidMachine

Lead In‑House Legal Counsel

Parkland, FL · Remote

Mobile advertising identifiers * Attribution technologies * Consent management frameworks * AI and machine learning use cases involving advertising data * Support implementation and governance of ...

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Showing results 21-40

All JobsMobile Machine Learning JobsMobile Machine Learning Jobs in Florida

Mobile Machine Learning information

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 Florida?

The most popular types of Machine Learning jobs in Florida are:

What are popular job titles related to Mobile Machine Learning jobs in Florida?

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

What job categories do people searching Mobile Machine Learning jobs in Florida look for?

The top searched job categories for Mobile Machine Learning jobs in Florida are:

What cities in Florida are hiring for Mobile Machine Learning jobs?

Cities in Florida with the most Mobile Machine Learning job openings:

Mobile Machine Learning jobs near you
Infographic showing various Mobile Machine Learning job openings in Florida as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Data Scientist

Altamira Technologies Corp.

Tampa, FL • On-site

Full-time

Posted 9 days ago

Key responsibilities

  • Design, implement, and maintain data pipelines to support data analysis and machine learning projects.

  • Interpret and analyze complex data sets using statistical and exploratory techniques, and develop models and algorithms to solve data challenges.

  • Coordinate with data engineers to build data environments, and utilize frameworks like Spark and Hadoop for large-scale data processing.

Job description

Altamira Technologies has a long and successful history providing innovative solutions throughout the U.S. National Security community.Headquartered in McLean, Virginia, Altamira serves the defense, intelligence and homeland security communities worldwide by focusing on creating innovative solutions leveraging common standards in architecture, data and security.Altamira believes that our people and the culture of our company differentiate us from other companies.

Position:Data Scientist (25% Travel)

Position Location:Fort Bragg, North Carolina

Position Description:
A data scientist will have skills sets of both data analysts and data engineers. Data scientists are responsible for designing, implementing, and maintaining a data pipeline.In addition, data scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning.

Data scientists must have a combination of skills that include programming, mathematical modeling, statistics, and domain knowledge. They must combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization.They must also be able to understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques. This postion requires 25% travel supporting the Mobile Training team.

Experience:

  • Interpret and analyze data using exploratory mathematics and statistical techniques based on the scientific method.
  • Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data
  • Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
  • Coordinate with Data Engineers to build Data environments providing data identified by other data professionals
  • Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
  • Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
  • Design and automate processes to facilitate the manipulation and analysis of data. Manage and integrate data across dissimilar data sets. Analyze large-scale structured and unstructured data.
  • Use frameworks such as Spark and Hadoop to conduct large-scale data processing. Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny.
  • Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages.
  • Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.
  • Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling.

Education:

  • Bachelor's degree in a STEM field is required.Master's degree is preferred in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.
  • Bachelor's degree is acceptable in the above fields if the incumbent has training and verifiable work experience in a related field.
  • Proficient with one or more programming languages (Java, C++, Python, R, etc.).
  • Proficient in Agile Development and Git Operations.
  • Demonstrated experience applying data science methods to real-world data problems.
  • TS/SCI clearance is preferred
  • Minimum SECRET Clearance to start with the willingness and ability to obtain TS/SCI.
Employment Type: Full Time

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