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Mobile Machine Learning Jobs in Maryland (NOW HIRING)

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Mobile Machine Learning information

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 Maryland?

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

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

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

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

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

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

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

Mobile Machine Learning jobs near you

SIPR Modernization Engineer and Analyst

AGE Solutions

Fort George G Meade, MD • On-site

Full-time

Posted 15 days ago

Job description

AGE Solutions is seeking a SIPR Modernization Engineer and Analyst to support our DoD customer in researching, evaluating, engineering, and integrating secure enterprise technologies supporting SIPRnet modernization and future DoD mission capabilities. The successful candidate will serve as a senior technical advisor supporting technology assessments, engineering studies, proof-of-concept activities, enterprise architecture initiatives, and modernization efforts across classified environments.

This position supports emerging technologies including cloud computing, Zero Trust Architecture, Enterprise Data Management, Artificial Intelligence (AI), DevSecOps, cloud federation, edge computing, coalition interoperability, and enterprise cybersecurity capabilities. The engineer will work collaboratively with multiple Directorates to develop secure, scalable, and resilient enterprise solutions supporting current and future operational requirements.

Responsibilities Include:

  • Conduct technical studies, research, engineering analyses, and technology assessments of current and future SIPRnet capabilities.
  • Identify, analyze, and evaluate emerging technologies supporting enterprise modernization initiatives.
  • Participate in technology demonstrations, pathfinders, laboratory evaluations, prototype development, and pilot programs.
  • Develop technical evaluation criteria, engineering plans, operational use cases, performance metrics, and assessment reports.
  • Support the modernization and consolidation of enterprise business systems and secure DoD networks.
  • Collaborate with DISA Directorates to design scalable, resilient, and secure enterprise architectures.
  • Design and evaluate Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and hybrid cloud solutions.
  • Assess commercial and government cloud technologies including Microsoft Azure Government, AWS GovCloud, and Microsoft 365 Government.
  • Support Cloud Federation initiatives enabling secure interoperability between DoD and coalition cloud environments.
  • Evaluate Cloud Access to the Edge technologies supporting disconnected, intermittent, and low-bandwidth (DIL) operational environments.
  • Support Enterprise Data Management (EDM) initiatives including data governance, data brokering, analytics, metadata management, and enterprise hosting services.
  • Engineer enterprise cybersecurity solutions aligned with DoD Zero Trust Architecture principles.
  • Evaluate and recommend Data Loss Prevention (DLP) and Digital Rights Management (DRM) technologies to protect sensitive and classified information.
  • Support modernization initiatives involving Command and Control (C2), Defense Collaboration Services (DCS), Coalition Integrated Environment (CIE), Knowledge as a Service (KAS), Managed Security Services (MSS), and Zero Trust (ZT).
  • Evaluate Software Defined Wide Area Network (SD-WAN) interoperability across multiple vendor platforms and DoD network domains.
  • Research, evaluate, and integrate Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), and intelligent automation capabilities.
  • Develop AI-enabled solutions supporting automated document classification, metadata tagging, workflow automation, and enterprise analytics.
  • Support DevSecOps initiatives by integrating security into continuous integration and continuous delivery (CI/CD) pipelines.
  • Evaluate Infrastructure as Code (IaC), configuration management, and automated deployment technologies.
  • Support secure mobile computing initiatives, mobile device management, and static and dynamic application security testing.
  • Participate in joint and coalition military exercises to evaluate emerging technologies in operational environments.
  • Prepare technical reports, engineering recommendations, executive briefings, and strategic roadmaps.
  • Provide technical leadership and mentorship to engineering teams supporting enterprise modernization initiatives.

Required Skills, Qualifications and Experience:

  • Minimum of 10 years of experience supporting DoD enterprise networking, systems engineering, cybersecurity, or cloud modernization initiatives.
  • DoD 8570/8140 IAT Level II Certification (Security+, CySA+, CCNA Security, or equivalent).
  • Must have and maintain a current DoD Top Secret clearance.
  • Candidates must reside within commutable distance of Fort Meade, MD in order to work onsite as required.
  • Experience supporting SIPRnet or other classified enterprise environments.
  • Experience performing technology evaluations, engineering studies, pilot programs, and proof-of-concept demonstrations.
  • Experience with cloud computing architectures including Azure Government, AWS GovCloud, Microsoft 365 Government, IaaS, PaaS, and SaaS.
  • Experience implementing or supporting Zero Trust Architecture.
  • Experience with Enterprise Data Management technologies.
  • Experience with networking, routing, switching, firewalls, IDS/IPS, and enterprise security architectures.
  • Experience with SD-WAN technologies and enterprise network modernization.
  • Experience with Palo Alto NGFW, ArcSight, FireEye, McAfee NSM, or similar cybersecurity platforms.
  • Experience with long-haul communications, mobile device management, NFC technologies, and Big Data platforms.
  • Experience supporting DevSecOps, CI/CD pipelines, Infrastructure as Code, and secure software development practices.
  • Experience with Artificial Intelligence, Machine Learning, or intelligent automation technologies.
  • Strong analytical, communication, and technical writing skills.
  • Demonstrated ability to independently lead engineering efforts, solve complex technical problems, and support executive decision-making.

Preferred Qualifications:

  • CISSP, CCSP, Azure Solutions Architect, AWS Solutions Architect, TOGAF, PMP, or equivalent certifications.
  • Experience supporting DISA, DoD, Joint Staff, Combatant Commands, or coalition operations.
  • Experience with Coalition Integrated Environment (CIE), Defense Collaboration Services (DCS), and Managed Security Services (MSS).
  • Experience integrating AI technologies into classified environments.
  • Experience supporting enterprise cloud federation and edge computing initiatives.
  • Experience supporting military exercises, operational demonstrations, and technology transition activities.
  • Experience briefing senior government leadership and technical review boards.

Work Environment and Physical Demand:

  • This position is performed primarily in a secure government facility supporting classified DoD information systems.
  • Daily activities involve prolonged computer use, participation in technical meetings, engineering reviews, laboratory evaluations, and collaboration with Government personnel.

The projected salary range for this position is $135,000+ annually. Final compensation will be determined based on factors including years of relevant experience, active security clearance level, certifications, technical skillset, contract requirements, and overall qualifications.

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