Job Description
We are seeking a visionary AI Infrastructure Architect to define the technological roadmap for our 2026 strategic initiatives. In this role, you will bridge the gap between cutting-edge machine learning research and robust, scalable production infrastructure. You will be responsible for architecting the systems that power our next-generation AI models, ensuring they are resilient, efficient, and ready for the demands of the future.
Join a team of elite engineers and data scientists pushing the boundaries of what is possible in artificial intelligence. If you are passionate about building the foundations of tomorrow's technology, we want to hear from you.
Responsibilities
- Architect Scalable AI Systems: Design and implement distributed computing architectures capable of handling petabyte-scale data processing.
- Optimize Workloads: Fine-tune GPU clusters and hardware acceleration strategies to maximize inference speed and reduce latency.
- Cloud Strategy: Lead the migration and management of AI workloads on AWS and GCP, ensuring cost-efficiency and high availability.
- Future-Proofing: Evaluate emerging technologies (e.g., Quantum Computing interfaces, Edge AI) to prepare infrastructure for 2026 and beyond.
- Collaborate with Data Science: Partner with ML engineers to translate model requirements into robust infrastructure specifications.
Qualifications
- Education: Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Experience: 5+ years of experience in DevOps, SRE, or Infrastructure Engineering within a high-scale tech environment.
- Technical Skills: Deep proficiency in Python, Kubernetes, Docker, and ML frameworks (TensorFlow, PyTorch).
- Cloud Mastery: Strong expertise in AWS (EC2, S3, SageMaker) or Google Cloud Platform (GKE, AI Platform).
- Problem Solving: Demonstrated ability to troubleshoot complex system failures and implement failover strategies.