Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to lead the architectural evolution of our systems, specifically targeting the technological milestones of 2026. You will be at the forefront of integrating cutting-edge Generative AI with scalable cloud infrastructure, ensuring our platforms are future-proofed for the next generation of digital interaction.
In this role, you will bridge the gap between research and production, deploying large-scale machine learning models that define the user experience of tomorrow. If you are passionate about building the backbone of the future and thrive in a high-performance environment, we want to hear from you.
Responsibilities
- Architect and maintain scalable MLOps pipelines designed for high-frequency AI inference.
- Lead the migration strategy towards edge computing solutions to support autonomous systems by 2026.
- Optimize data throughput and model latency across distributed cloud environments.
- Collaborate with R&D teams to integrate emerging technologies into our core infrastructure.
- Ensure system security and compliance for handling sensitive predictive data.
- Develop automation scripts (Python/Terraform) to streamline deployment processes.
Qualifications
- 7+ years of experience in DevOps, Site Reliability Engineering, or MLOps.
- Deep expertise in Python, Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
- Proven track record of deploying and managing Large Language Models (LLMs) at scale.
- Strong understanding of distributed systems theory and real-time data processing.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.
- Experience with CI/CD pipelines and infrastructure-as-code practices.