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Edge Computing Jobs in Maryland (NOW HIRING)

Renesas Electronics

Senior Staff AI Engineer

Columbia, MD · On-site

$103K - $142K/yr

Proficiency in Python, MATLAB, and C, specifically including experience with real-time edge computing and embedded systems. * Background in digital signal processing (DSP) for audio and time-series ...

Renesas Electronics

Senior Staff AI Engineer

Columbia, MD

$103K - $142K/yr

Proficiency in Python, MATLAB, and C, specifically including experience with real-time edge computing and embedded systems. * Background in digital signal processing (DSP) for audio and time-series ...

Renesas Electronics

Senior Staff AI Engineer

Columbia, MD

$103K - $142K/yr

Proficiency in Python, MATLAB, and C, specifically including experience with real-time edge computing and embedded systems. * Background in digital signal processing (DSP) for audio and time-series ...

Cymertek

Cloud Automation Engineer

Annapolis Junction, MD · On-site

$57 - $76/hr

Knowledge of edge computing frameworks * Expertise in integrating DevSecOps practices PLUG IN to CYMERTEK - And design your future... YOUR FOREVER CAREER STARTS HERE Are you looking for more than ...

Sealing Technologies

Solutions Architect

Columbia, MD · On-site

$105K - $135K/yr

... edge computing environments. This role is ideal for someone who understands server architecture at a low level CPU, memory, storage, networking, power, and thermal constraints and can translate that ...

The Swift Group, LLC

DevOps Engineer

Columbia, MD · On-site

$51.25 - $70.25/hr

... portable edge-computing infrastructure to non-cloud (on-premise) environments • Diagnose and resolve system issues across the stack, including networking, containers, and cloud services • ...

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How much do edge computing jobs pay per hour?

As of Aug 9, 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.

What are edge computing jobs?

Edge computing jobs involve designing, deploying, and maintaining computing infrastructure at or near data sources to reduce latency and improve performance. Roles often require knowledge of networking, cloud platforms, and programming languages like Python or C++, with certifications such as Cisco or AWS sometimes preferred.

What are the key skills and qualifications needed to thrive in edge computing?

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 professional?

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 does an edge computing professional do?

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
Infographic showing various Edge Computing job openings in Maryland as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $51,589 per year, or $24.8 per hour.

Postdoctoral Fellow - Atomistic Simulations and AI for Materials Design

Johns Hopkins University

Baltimore, MD • On-site

$48K - $66K/yr

Full-time

Re-posted 20 days ago

Johns Hopkins University rating

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

186th of 617 rated colleges and universities

Job description

Description
The AtomGPTLab, led by Dr. Kamal Choudhary at Johns Hopkins University, invites applications for a Postdoctoral Fellow position in the fields of atomistic simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical molecular simulations, and cutting-edge AI techniques including graph neural networks (GNNs) and large language models (LLMs) to accelerate experimental design and discovery of novel materials.
The research spans quantum mechanics, statistical physics, and deep learning, and aims to enable AI-guided predictions of synthesizable and functional materials such as superconductors, catalysts, semiconductors, and energy-relevant compounds. The position is embedded in an interdisciplinary and collaborative environment with active interactions across experimental groups and national laboratories.
Qualifications
Basic Qualifications or Specialized Certifications
  • A PhD in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science, or a related field.
  • Demonstrated experience in one or more of the following: Density Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs).

Extensive Knowledge In:
  • First-principles simulations with packages such as VASP, Quantum ESPRESSO, GPAW.
  • Machine-learned interatomic potentials (e.g., ALIGNN-FF).
  • Structure-property prediction using GNNs (e.g., ALIGNN,).
  • LLM fine-tuning and prompt engineering (e.g., HuggingFace, OpenAI, AtomGPT).

Working Knowledge Of:
  • Workflow tools (e.g.,JARVIS-Tools, ASE) and HPC environments.
  • Software development in Python, Git-based version control, and Conda packaging.
  • Data integration and surrogate modeling using experimental and computational datasets.
  • Interdisciplinary collaboration and mentoring of students or junior researchers.

Specific Duties & Responsibilities
  • Conduct high-throughput DFT calculations and manage large-scale materials datasets.
  • Develop GNN architectures for predicting materials properties from atomic graphs.
  • Train and deploy machine-learned force fields for MD simulations and rapid screening.
  • Fine-tune or pre-train LLMs for generation and analysis of materials structures, synthesis protocols, and characterization outputs.
  • Build pipelines for combining experimental and simulated data for inverse design.
  • Provide real-time computational feedback to experimental collaborators for synthesis and characterization.
  • Lead manuscript writing, conference presentations, and contributions to open-source repositories.
  • Mentor undergraduate and graduate students, and participate in grant proposal development.

Additional Opportunities
  • Collaborate as Co-PI on interdisciplinary proposals.
  • Engage with experimental groups, national labs, and industry partners.
  • Participate in the development of open cyberinfrastructure (e.g., AtomGPT.org).
  • Attend international conferences and contribute to global research communities.
  • Access to cutting-edge computing clusters and experimental characterization tools.

Application Instructions
Applicants should submit a curriculum vitae and three recent publications. Review of applications will begin in mid-August 2025.

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About Johns Hopkins University

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Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty members, along with their colleagues at the university’s Applied Physics Laboratory, have made us the nation’s leader in federal research and development funding every year since 1979. That’s a fitting distinction for America’s first research university, a place that has revolutionized higher education in the U.S. and continues to bring knowledge and discoveries to the world.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Baltimore, MD, US

Year founded

1876

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