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Mid Level Neuromorphic Computing Jobs in West Virginia

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Mid Level Neuromorphic Computing information

What are mid level neuromorphic computing professionals?

Mid level neuromorphic computing professionals are specialists with several years of experience who design, develop, and optimize hardware and software systems inspired by the structure and function of the human brain. They typically work on building and programming neuromorphic chips, developing algorithms that mimic neural processes, and integrating these systems into real-world applications such as robotics or edge computing. Their expertise bridges neuroscience, computer engineering, and artificial intelligence, and they often collaborate with interdisciplinary teams to advance brain-inspired computing technologies.

What are some common challenges faced by professionals in mid-level neuromorphic computing roles, and how can they be addressed?

Professionals in mid-level neuromorphic computing roles often encounter challenges such as integrating novel hardware with existing software systems, managing the complexity of neural-inspired algorithms, and keeping pace with rapid advancements in the field. Collaborating closely with multidisciplinary teams—including hardware engineers, data scientists, and neuroscientists—can help address these challenges. Additionally, staying updated on the latest research and industry trends, as well as participating in collaborative projects, can enhance problem-solving skills and foster innovation in this evolving area.

What is the difference between Mid Level Neuromorphic Computing vs Mid Level Machine Learning Engineer?

AspectMid Level Neuromorphic ComputingMid Level Machine Learning Engineer
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related field; knowledge of neuromorphic hardwareBachelor's in Computer Science, Data Science, or related; experience with ML frameworks
Work EnvironmentResearch labs, hardware development, AI hardware companiesTech companies, startups, data-driven organizations
Industry UsageAI hardware, neuromorphic chip design, cognitive computingSoftware development, AI applications, data analysis

Mid Level Neuromorphic Computing professionals focus on hardware and cognitive architectures inspired by the brain, often working with specialized hardware and research teams. In contrast, Mid Level Machine Learning Engineers develop algorithms and models primarily in software to solve data-driven problems. Both roles require a strong technical background but differ in their focus on hardware versus software applications.

What are the key skills and qualifications needed to thrive as a Mid Level Neuromorphic Computing Engineer, and why are they important?

To thrive as a Mid Level Neuromorphic Computing Engineer, you need a solid background in computer engineering, neuroscience, and machine learning, usually supported by a relevant degree and experience with neural network architectures. Familiarity with tools like Python, MATLAB, TensorFlow, and simulation platforms such as NEST or SpiNNaker, along with knowledge of specialized hardware, is typically required. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share complex ideas with multidisciplinary teams. These skills and qualifications are crucial for developing advanced neuromorphic systems that bridge neuroscience and AI, pushing the boundaries of efficient computing.
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Mid Level Neuromorphic Computing jobs near you
Cloud Architect (Mid-level) with Security Clearance

Cloud Architect (Mid-level) with Security Clearance

22nd Century Technologies, Inc.

Clarksburg, WV • On-site

$150K - $160K/yr

Other

Posted 13 days ago

Job description

Cloud Solutions Architect (Mid)
Location: Clarksburg, WV Onsite
Availability: Immediate Salary Range: $150,000 – 160,000 Job Description About the Role
The Cloud Solutions Architect (Mid) is responsible for designing, implementing, and optimizing cloud-based infrastructure and application architecture that meet organizational and mission requirements. This role translates business and technical needs into scalable, secure, and cost-effective cloud solutions across public, private, and hybrid environments.
The Cloud Solutions Architect partners with development teams, operations staff, and stakeholders to define cloud migration strategies, establish architectural standards, and ensure compliance with security and governance policies. The ideal candidate brings hands-on experience with major cloud platforms and a strong understanding of enterprise architecture principles.
You Will
• Design and implement cloud architectures across AWS, Azure, or GCP that align with organizational requirements for scalability, availability, and security.
• Develop cloud migration strategies and roadmaps, including assessment of existing on-premises workloads for cloud readiness.
• Define and enforce cloud architectural standards, design patterns, and best practices across project teams.
• Collaborate with DevOps, security, and development teams to ensure seamless integration of cloud services into CI/CD pipelines and application workflows.
• Evaluate and recommend cloud services, tools, and third-party solutions to optimize performance and reduce costs.
• Implement infrastructure-as-code (IaC) solutions using tools such as Terraform, CloudFormation, or ARM templates.
• Ensure cloud environments comply with applicable security frameworks (FedRAMP, NIST 800-53, FISMA) and data protection requirements.
• Conduct architecture reviews, proof-of-concept initiatives, and technical presentations for stakeholders.
• Monitor cloud resource utilization and recommend optimization strategies for cost management and performance tuning.
• Document cloud architectures, design decisions, and operational procedures.
Desired Skills and Experience
• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 4–7 years of experience in cloud architecture, cloud engineering, or infrastructure roles.
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP), including core compute, storage, networking, and identity services.
• Experience with infrastructure-as-code tools (Terraform, CloudFormation, Pulumi, or equivalent).
• Working knowledge of containerization technologies (Docker, Kubernetes, ECS/EKS).
• Familiarity with cloud security principles, identity and access management (IAM), and network security controls.
• Understanding of microservices architecture, API gateway patterns, and serverless computing.
• Cloud certification preferred (e.g., AWS Solutions Architect Associate, Azure Solutions Architect Expert, GCP Professional Cloud Architect).
• Strong analytical, communication, and documentation skills.
• Experience in government or DoD cloud environments (e.g., GovCloud, IL5/6) is a plus.
Security Clearance
• Active TS/SCI (willing to get CI poly)

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