AI Infrastructure Engineer (The AI Backbone Builder)

Unreal Gigs - Austin, TX

Full-time - Mid Level

Remote - Austin, TX

About the position

The AI Infrastructure Engineer, also known as The AI Backbone Builder, is responsible for designing, deploying, and maintaining the infrastructure that supports AI innovation. This role involves creating scalable, high-performance systems that facilitate machine learning model training and real-time inference, ensuring efficient and secure operation of AI systems across the organization.

Responsibilities

• Architect and implement scalable infrastructure that supports AI workloads, including machine learning model training, large-scale data processing, and real-time inference.
• 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.
• Implement strategies to optimize compute resources for AI workloads, including GPU/TPU provisioning, memory management, and parallel processing.
• Manage cloud-based AI platforms (AWS, GCP, Azure) as well as on-premise infrastructure for AI development, handling infrastructure as code (IaC) and container orchestration (Docker, Kubernetes).
• Implement and maintain CI/CD pipelines for machine learning models to enable rapid experimentation, testing, and deployment.
• Ensure that the AI infrastructure complies with security best practices and regulatory requirements, implementing robust access controls and encryption.
• Continuously monitor the health and performance of AI infrastructure, identifying bottlenecks, reducing latency, and troubleshooting issues.

Requirements

• Deep experience in designing and building infrastructure that supports AI and machine learning workloads.
• Strong experience with cloud platforms like AWS, GCP, or Azure, particularly with AI services and infrastructure management.
• Expertise in automating infrastructure provisioning and model deployment using tools such as Terraform, Ansible, Jenkins, or GitLab CI.
• Hands-on experience with GPU/TPU optimization for machine learning and deep learning tasks.
• Strong understanding of security best practices, including data encryption, access management, and compliance with regulations like GDPR and HIPAA.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience in AI infrastructure or DevOps.

Nice-to-haves

• Certifications in cloud platforms (AWS, GCP, Azure) or DevOps tools are a plus.

Benefits

• Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
• Competitive vacation, sick leave, and 20 paid holidays per year.
• Flexible work schedules and telecommuting options.
• Opportunities for training, certification reimbursement, and career advancement programs.
• Access to wellness programs, including gym memberships, health screenings, and mental health resources.
• Life insurance and short-term/long-term disability coverage.
• Confidential counseling and support services for personal and professional challenges.
• Financial assistance for continuing education and professional development.
• Opportunities to participate in community service and volunteer activities.
• Employee recognition programs to celebrate achievements and milestones.