Remote opportunity at
EdgeQ Technologies Private LimitedAI Infrastructure Specialist
EdgeQ Technologies Private Limited seeks an AI Infrastructure Specialist for a full-time, fully remote position within the United States. This role focuses on engineering, building, launching,…
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About This Role
EdgeQ Technologies Private Limited seeks an AI Infrastructure Specialist for a full-time, fully remote position within the United States. This role focuses on engineering, building, launching, and sustaining robust infrastructure designed for machine learning and artificial intelligence workloads. Professionals suited for this role will possess a background in DevOps, cloud systems, or AI infrastructure, with a strong emphasis on GPU computing and container management. The chosen specialist will handle cloud-based…
Job Description
EdgeQ Technologies Private Limited seeks an AI Infrastructure Specialist for a full-time, fully remote position within the United States. This role focuses on engineering, building, launching, and sustaining robust infrastructure designed for machine learning and artificial intelligence workloads. Professionals suited for this role will possess a background in DevOps, cloud systems, or AI infrastructure, with a strong emphasis on GPU computing and container management.
The chosen specialist will handle cloud-based platforms like AWS, Microsoft Azure, and Google Cloud, while configuring high-performance computing environments for AI tasks. Responsibilities include building MLOps pipelines, managing Kubernetes clusters, implementing security protocols, and tuning resource utilization across CPU, memory, and storage. Collaboration with machine learning engineers, AI researchers, and DevOps personnel is a core component of daily operations.
Responsibilities
- Design and deploy scalable infrastructure supporting artificial intelligence and machine learning operations
- Manage cloud environments across Google Cloud, Microsoft Azure, and Amazon Web Services
- Configure and optimize GPU computing environments specifically for AI workloads
- Implement and maintain Docker containers alongside Kubernetes clusters
- Support environments dedicated to AI model training, deployment, and inference
- Construct and sustain MLOps pipelines for continuous integration and deployment
- Track infrastructure performance, resource utilization, availability, and scalability
- Optimize storage, memory, CPU, and GPU resources for artificial intelligence tasks
- Build automation tools utilizing technologies such as Ansible or Terraform
- Collaborate directly with DevOps staff, AI engineers, and machine learning specialists
- Deploy access controls, security measures, and monitoring solutions
- Resolve infrastructure failures and guarantee systemic reliability
- Document technical processes and uphold infrastructure best practices
Requirements
- Two to six years of professional experience in cloud infrastructure, AI infrastructure, DevOps, or a closely related field
- Demonstrated expertise with Google Cloud, Microsoft Azure, or Amazon Web Services platforms
- Practical, hands-on experience utilizing Kubernetes and Docker
- Familiarity with AI workload optimization and GPU computing principles
- Competency in Linux administration and system troubleshooting
- Knowledge of Shell scripting, Bash, or Python
- Familiarity with inference workflows and machine learning model deployment
- Experience implementing infrastructure automation and CI/CD pipelines
- Proficiency with infrastructure tools such as Ansible or Terraform
- Comprehension of cloud security, storage, and networking fundamentals
- Experience working with monitoring platforms like Datadog, Grafana, or Prometheus
- Strong problem-solving, analytical, and troubleshooting capabilities
- Legal authorization to work in the United States
Qualifications
- Bachelor's or Master's degree in Engineering, Information Technology, Computer Science, or a related discipline
- Experience managing environments with NVIDIA GPUs, CUDA, and GPU resource management
- Familiarity with MLOps frameworks including Ray, Kubeflow, or MLflow
- Knowledge regarding large language model deployment and inference optimization
- Experience working with high-performance computing and distributed computing systems
- Familiarity with microservices architecture and serverless AI infrastructure
- Understanding of model serving frameworks like TorchServe, vLLM, or NVIDIA Triton
- Experience managing large-scale artificial intelligence infrastructure environments
Core Skills
Benefits
- Annual salary ranging from $95,000 to $155,000 USD
- Competitive compensation determined by expertise and experience
- 100% remote work opportunity across eligible locations in the United States
- Flexible working arrangements
- Vision, dental, and health insurance
- Paid time off and holidays
- Retirement savings benefits where applicable
- Support for professional development and technical certifications
- Opportunities for career advancement
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, this is a 100% remote position open to qualified candidates located within the United States who can collaborate across different US time zones.
What is the salary range for the AI Infrastructure Specialist role?
The annual salary range is $95,000 to $155,000 USD, with compensation determined based on technical expertise and experience.
How many years of experience are required?
Applicants must have between two and six years of professional experience in cloud infrastructure, AI infrastructure, DevOps, or a related area.
What benefits are provided with this job?
Benefits include health, dental, and vision insurance, paid time off and holidays, retirement savings benefits where applicable, flexible working arrangements, and technical certification and professional development support.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.