AI Infrastructure Systems Developer
3 weeks ago
Job Overview
ZipRecruiter is seeking an experienced American I.A. Infrastructure Systems Developer to join our team in the United States, with a salary range of $170,000 - $200,000 per year.
The successful candidate will be responsible for designing and building infrastructure that supports cutting-edge AI solutions, working closely with data scientists and software engineers to ensure seamless deployments and continuous delivery of AI models into production environments.
About the Role
We're looking for a skilled professional with 3+ years of experience in infrastructure engineering, particularly in building and maintaining AI or machine learning infrastructure in production environments. The ideal candidate will have a strong background in cloud services, containerization, and orchestration tools, as well as expertise in optimizing infrastructure for AI workloads.
Key Responsibilities
- Design and Build AI Infrastructure: Architect and implement scalable infrastructure that supports AI workloads, including machine learning model training, large-scale data processing, and real-time inference.
- Support AI Model Development and Deployment: Collaborate with data scientists and engineers to build pipelines that automate the end-to-end machine learning lifecycle, from data ingestion to model training, deployment, and monitoring.
- Optimize AI Workloads for Performance: Implement strategies to optimize compute resources for AI workloads, including GPU/TPU provisioning, memory management, and parallel processing.
- Cloud and On-Premise Infrastructure Management: Manage cloud-based AI platforms (AWS, GCP, Azure) as well as on-premise infrastructure for AI development, handling everything from infrastructure as code (IaC) to container orchestration (Docker, Kubernetes).
- Automation and Continuous Integration/Deployment (CI/CD): Implement and maintain CI/CD pipelines for machine learning models to enable rapid experimentation, testing, and deployment.
- Security and Compliance: Ensure that the AI infrastructure complies with security best practices and regulatory requirements, implementing robust access controls, encryption, and other security measures to protect sensitive data and AI models.
Requirements
- Required Skills and Qualifications
- AI Infrastructure Expertise: Deep experience in designing and building infrastructure that supports AI and machine learning workloads.
- Cloud Platforms and Tools: Strong experience with cloud platforms like AWS, GCP, or Azure, particularly with AI services and infrastructure management.
- Automation and DevOps: Expertise in automating infrastructure provisioning and model deployment using tools such as Terraform, Ansible, Jenkins, or GitLab CI.
- GPU/TPU Optimization: Hands-on experience with GPU/TPU optimization for machine learning and deep learning tasks.
- Security and Compliance: Strong understanding of security best practices, including data encryption, access management, and compliance with regulations like GDPR and HIPAA.
- Educational Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- Certifications in cloud platforms (AWS, GCP, Azure) or DevOps tools are a plus.
- Experience Requirements
- 3+ years of experience in infrastructure engineering, with a focus on building and maintaining AI or machine learning infrastructure in production environments.
- Proven experience with cloud services, containerization, orchestration tools, and optimizing infrastructure for AI workloads.
- Experience working with data scientists and machine learning engineers to support model development, testing, and deployment.
Benefits
- Comprehensive Benefits Package, including health insurance, paid time off, and wellness programs.
- Professional Development Opportunities, including training, certification reimbursement, and career advancement programs.
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