AI Infrastructure Architect

3 weeks ago

San Francisco, California, United States Unreal Gigs Full time
Transformative AI Infrastructure Leader

We are seeking an exceptional AI Infrastructure Architect to spearhead the development and implementation of cutting-edge AI infrastructure solutions. This visionary role demands a strategic leader who can harmonize technology advancements with business objectives, ensuring seamless integration of AI capabilities across our organization.

About the Role:
  • Salary Range: $180,000 - $250,000 per annum, depending on experience and qualifications
  • Location: Unreal Gigs HQ, USA (remote work options available)

Key Responsibilities:

  1. Spearheading AI Infrastructure Vision: Develop and execute a comprehensive strategy for AI infrastructure, aligning it with our company's goals and objectives. This involves prioritizing areas that enhance scalability, reduce latency, and optimize resource usage to support AI-driven innovation.
  2. Leading Scalable Data Pipelines: Oversee the design, development, and maintenance of data pipelines that enable real-time data processing and batch analytics. Ensure that data is readily available, secure, and accessible to AI teams for training, testing, and deployment.
  3. Optimizing Compute Resources: Manage the infrastructure required for high-performance computing, including GPU clusters, cloud resources, and storage systems. Maximize cost-efficiency, minimize latency, and optimize computational resources for AI workloads.
  4. Enabling Scalable AI Model Deployment: Develop frameworks for model deployment, monitoring, and versioning across production environments. Ensure that deployed models are robust, scalable, and maintain high availability for end-users.
  5. Collaborating with Security and Compliance Teams: Work closely with cybersecurity and compliance teams to enforce data privacy, security protocols, and regulatory compliance. Implement best practices to safeguard data integrity and meet industry standards for AI systems.
  6. Driving Automation and CI/CD: Implement CI/CD pipelines and automation for model testing, deployment, and updates. Streamline processes that enable rapid iteration, reducing time to market for AI solutions and enhancing productivity for AI teams.
  7. Staying Up-to-Date on Emerging Technologies: Keep up with advancements in infrastructure technology, including containerization, distributed computing, and serverless architecture. Integrate new solutions and best practices to maintain a competitive, forward-looking infrastructure.

Requirements and Qualifications:

  • Ai Infrastructure Expertise: Extensive experience designing, managing, and scaling AI infrastructure, including data pipelines, compute resources, and cloud services. Proficient in creating infrastructure that supports data processing, high-performance computing, and large-scale deployments.
  • High-Performance Computing and Cloud Platforms: Expertise in high-performance environments, including experience with cloud platforms (AWS, GCP, Azure), GPU clusters, and distributed computing. Understand how to maximize computational efficiency for AI workloads.
  • Data Architecture and Security Knowledge: Strong understanding of data architecture, ETL processes, and data governance. Skilled at creating secure, compliant data pipelines that support the demands of AI research and applications.
  • Automation and CI/CD for Ai: Experience implementing CI/CD pipelines, automation tools, and containerization technologies (Docker, Kubernetes). Know how to streamline workflows for rapid testing, deployment, and scaling of AI models.
  • Strategic Vision and Collaboration: Proven ability to develop a strategic vision for AI infrastructure and work collaboratively with cross-functional teams, including AI researchers, data engineers, and security professionals. Understand how to align infrastructure with organizational goals.

Educational Requirements:

  • Masters or Ph.D. in Computer Science, Data Engineering, Cloud Computing, or a related field. Equivalent experience in AI infrastructure and platform engineering may be considered.
  • Certifications in cloud computing, data engineering, or infrastructure management (e.g., AWS Certified Solutions Architect, Google Cloud Professional Data Engineer) are advantageous.

Experience Requirements:

  • 10+ years of experience in infrastructure engineering, cloud computing, or a similar field, with a proven track record of building infrastructure for AI and machine learning applications.
  • 5+ years of experience in a leadership role, managing teams in AI infrastructure, data architecture, or high-performance computing environments.
  • Familiarity with regulatory requirements and compliance standards in data security and privacy is highly desirable.

Benefits:

  • Comprehensive Medical, Dental, and Vision Insurance Plans
  • Paid Time Off 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 and Disability Insurance
  • Employee Assistance Program (EAP) for Confidential Counseling and Support Services
  • Tuition Reimbursement for Continuing Education and Professional Development
  • Community Engagement Opportunities for Volunteering and Community Service

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