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Edge Computing Jobs in Maryland (NOW HIRING)

NTT DATA Services

The IoT / Edge Architect

Bethesda, MD · On-site +1

$67.50 - $88.75/hr

The IoT / Edge Architect will serve as the technical lead for the design, integration, and management of secure, scalable IoT and edge computing solutions supporting the client. This role is ...

NTT DATA Services

The IoT / Edge Architect

MD · Remote

$67.50 - $88.75/hr

The IoT / Edge Architect will serve as the technical lead for the design, integration, and management of secure, scalable IoT and edge computing solutions supporting the client. This role is ...

NTT DATA Services

IoT / Edge Software Engineer

MD · Remote

$68K - $141K/yr

This role is essential for delivering a robust, secure, and resilient edge computing infrastructure that enables client to provide accurate, timely, and actionable radiation exposure data across ...

Renesas Electronics

Senior Staff AI Engineer

Columbia, MD · On-site

$101K - $139K/yr

... time edge computing and embedded systems. Preferred : • Background in digital signal processing (DSP) for audio and time-series data preferred. Company : Renesas is an embedded semiconductor ...

Cherry Bekaert

Senior Hardware Architect

Columbia, MD · On-site

Exposure to edge computing or GPU-based platforms (NVIDIA, AI/ML) * Background in rugged or mission-critical environments * Any experience working directly with customers or gathering requirements ...

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How much do edge computing jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for edge computing in Maryland is $24.80, according to ZipRecruiter salary data. Most workers in this role earn between $19.13 and $29.18 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

Edge computing jobs such as network engineers, cybersecurity specialists, and systems architects are likely to persist as they require complex problem-solving, infrastructure management, and security expertise that are difficult for AI to fully automate. These roles involve designing, maintaining, and securing distributed systems, often requiring certifications and hands-on experience. Skills in cloud platforms, programming, and real-time data analysis will remain valuable in this field.

Does edge computing have a future?

Edge computing is a growing field with increasing adoption across industries such as manufacturing, healthcare, and IoT, creating demand for professionals skilled in network architecture, security, and cloud integration. As data processing needs expand and latency requirements grow, job opportunities in this area are expected to increase steadily in the coming years.

Does Tesla use edge computing?

Tesla employs edge computing in its vehicles to process data locally for features like Autopilot and real-time diagnostics, reducing reliance on cloud servers. This approach enhances response times and system reliability, which are critical for autonomous driving and vehicle safety systems.

What is the highest paying computing job?

In the field of edge computing, senior roles such as solutions architect, cloud engineer, or systems architect tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in distributed systems, networking, and cloud platforms, along with relevant certifications like AWS or Cisco. Salary levels depend on experience, location, and company size.

What are the key skills and qualifications needed to thrive in the Edge Computing position, and why are they important?

To excel in Edge Computing, you need a solid background in distributed systems, network engineering, and real-time data processing, typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools and platforms such as Docker, Kubernetes, IoT frameworks, and edge-specific cloud solutions, along with relevant certifications like CompTIA IoT+ or Cisco certifications, is highly advantageous. Strong problem-solving skills, adaptability, and effective communication are crucial soft skills for collaborating across technical and business teams. These skills ensure effective design, deployment, and maintenance of decentralized computing solutions that drive innovation and performance in various industries.

What is an Edge Computing job?

An Edge Computing job involves designing, deploying, and managing computing resources closer to the data source to reduce latency and improve real-time data processing. Professionals in this field work with distributed computing, networking, and security to ensure efficient and reliable performance of edge devices. Roles often include Edge Engineer, Edge Architect, or IoT Specialist, requiring expertise in cloud-native technologies, AI, and edge infrastructure. These jobs are critical in industries like healthcare, manufacturing, and autonomous systems where low-latency decision-making is essential.

What are typical daily responsibilities of an Edge Computing professional?

As an Edge Computing professional, your daily tasks often include designing and deploying edge infrastructure, optimizing real-time data processing pipelines, and monitoring system performance to ensure low latency operations. You may coordinate with software developers, hardware engineers, and security specialists to integrate edge devices with cloud services. Troubleshooting network and latency issues, updating firmware, and implementing security protocols are also regular parts of the role. This multidisciplinary environment allows you to see immediate impacts from your work while constantly collaborating with cross-functional teams to solve complex problems.

What are the most commonly searched types of Edge Computing jobs in Maryland? The most popular types of Edge Computing jobs in Maryland are:
What are popular job titles related to Edge Computing jobs in Maryland? For Edge Computing jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Edge Computing jobs in Maryland look for? The top searched job categories for Edge Computing jobs in Maryland are:
Edge Computing jobs near you
Edge AI/Model Optimization Engineer

Edge AI/Model Optimization Engineer

NextGen Federal Systems

Aberdeen, MD

$123K - $147K/yr

Full-time

Re-posted 28 days ago

Job description

NextGen is seeking a highly motivated and technically skilled Edge AI/Model Optimization Engineer to support the deployment, optimization, and sustainment of AI and agentic AI capabilities within edge and tactical computing environments. This role focuses on evaluating, tuning, benchmarking, and operationalizing Large Language Models (LLMs), embedding models, and AI inference services for constrained hardware platforms, including the X9 Spider Mission Computer architecture and other edge compute systems supporting operational missions using ReadiChat.

ReadiChat is a mission-focused, agentic AI platform designed to help organizations build, deploy, govern, and scale specialized AI agents for operational workflows. It combines AI agents, workflow orchestration, grounded knowledge, testing frameworks, and enterprise controls into a single collaborative workspace.

The ideal candidate will possess expertise in AI model optimization, GPU-enabled edge computing, runtime performance tuning, and operational AI deployment. This role requires close collaboration with AI engineers, systems integrators, mission stakeholders, and operational users to ensure AI-enabled capabilities remain performant, reliable, and mission-effective within disconnected, degraded, intermittent, and low-bandwidth environments.

Responsibilities
  • Evaluate candidate Large Language Models (LLMs), embedding models, and AI inference solutions for quality, latency, memory utilization, reliability, and operational performance on embedded GPU-enabled edge compute platforms, including the X9 Spider Mission Computer architecture.
  • Tune and optimize AI model runtime configurations for edge deployment, including quantization strategies, batching configurations, context window sizing, cache behavior, inference scheduling, and GPU memory utilization specific to operational edge hardware environments.
  • Collaborate with customer stakeholders to assess mission requirements and evaluate alternative edge compute platforms when operational demands exceed X9 Spider capabilities or when cost, performance, power, size, weight, or thermal tradeoffs require additional analysis.
  • Benchmark agentic AI workflows, inference pipelines, and model-serving architectures against target hardware constraints and operational performance thresholds.
  • Recommend model-selection, runtime, and configuration tradeoffs balancing mission effectiveness, latency, throughput, resource utilization, reliability, and operational sustainability.
  • Build and maintain repeatable performance and stress-testing frameworks for evaluating latency, throughput, tool-call overhead, failover behavior, degraded-resource conditions, and disconnected operational scenarios on edge compute platforms.
  • Package, deploy, validate, and sustain local model-serving components and inference services to support reliable operation within tactical and edge environments.
  • Collaborate with agent engineers, AI developers, and integration teams to validate that agent behavior, workflow reliability, and operational outcomes remain acceptable following model compression, quantization, runtime optimization, or hardware configuration changes.
  • Support deployment, troubleshooting, optimization, and sustainment activities for AI-enabled applications operating in edge, airborne, tactical, or disconnected operational environments.
  • Train customer technical personnel on supported model profiles, operational constraints, runtime tuning considerations, deployment limitations, troubleshooting procedures, and platform sustainment best practices.
  • Maintain technical documentation, benchmarking results, model validation reports, deployment procedures, optimization baselines, configuration guides, and operational support materials.
  • Support DevSecOps and CI/CD activities associated with AI model packaging, deployment automation, runtime validation, and operational release processes.
Required Qualifications
  • Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, Data Science, Artificial Intelligence, or related technical discipline.
  • 5+ years of experience supporting AI/ML deployment, model optimization, edge computing, GPU acceleration, or AI inference operations.
  • Experience deploying and optimizing LLMs, embedding models, or AI inference pipelines within resource-constrained or edge-compute environments.
  • Experience with GPU-enabled systems and inference optimization technologies such as CUDA, TensorRT, ONNX Runtime, vLLM, Ollama, or equivalent platforms.
  • Experience tuning AI runtime configurations including quantization, batching, caching, and memory optimization techniques.
  • Experience benchmarking AI models and operational workflows against hardware performance constraints.
  • Experience with Linux-based systems, containerized deployments, and orchestration technologies such as Docker and Kubernetes.
  • Familiarity with Python and AI/ML deployment frameworks commonly used for edge inference and operational AI systems.
  • Strong analytical, troubleshooting, and performance optimization skills.
  • Ability to communicate technical findings and operational tradeoffs effectively to technical and non-technical stakeholders.
  • Active Security Clearance is required
Desired Qualifications
  • Experience supporting tactical, airborne, or mission-command edge computing environments.
  • Familiarity with X9 Spider Mission Computer architectures or similar embedded GPU-enabled mission systems.
  • Experience supporting AI-enabled workflows within NGC2, AIDP, EMSCO, Lattice, or related operational ecosystems.
  • Experience with model quantization techniques such as INT8, FP16, GGUF, GPTQ, AWQ, or similar optimization approaches.
  • Familiarity with disconnected, degraded, intermittent, and low-bandwidth (DDIL) operational environments.
  • Experience with hardware evaluation and performance trade studies for operational edge compute systems.

About NextGen:

NextGen Federal Systems is an innovative technology and professional services provider specializing in advanced software solutions and comprehensive mission and business support services. We work in close collaboration with our customers to truly understand their business and mission goals. Our approach is to design, build, implement, and manage solutions that measurably improve our client's organizational performance. We have established and foster a corporate culture where we:

  • Treat employees with fairness and respect regardless of their position, sexual identity, race, or tenure.
  • Communicate the importance of our mission and our employees' contributions to it, ensuring they understand how their job role contributes to the greater good.
  • Openly promote and communicate our ideas for change and adaptability.
  • Strive to achieve results as an organization.
  • Hold employees accountable to their commitments and provide incentives that encourage positive and productive behaviors.
  • Value the talents and contributions of our employees as the key factor for our success.
  • Create an environment where people can engage at all levels.
  • Encourage people to take risks and allow them to make mistakes.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities.

RefID: A01

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