Job Description
We are at the forefront of the technological revolution, building the infrastructure that will define the era of 2026 and beyond. As a Senior AI Infrastructure Engineer at Nexus Future Systems, you will architect the scalable, resilient backbone required to support our next-generation artificial intelligence models. This is not just a job; it is an opportunity to shape the digital landscape of tomorrow.
You will be responsible for designing and maintaining the complex ecosystem that powers our proprietary algorithms. If you are passionate about high-performance computing, cloud architecture, and solving the hardest engineering challenges of the future, we want to hear from you.
Responsibilities
- Architect Scalable MLOps Pipelines: Design end-to-end machine learning infrastructure that supports massive data throughput and real-time model training.
- Optimize Cloud Resources: Engineer cost-effective and high-performance solutions on AWS and GCP to minimize latency and maximize efficiency.
- Implement Edge Computing: Develop distributed systems that bring AI inference capabilities closer to the data source for ultra-low latency.
- Ensure System Resilience: Build automated monitoring and disaster recovery systems to guarantee 99.99% uptime for critical AI services.
- Cross-Functional Collaboration: Partner with Data Scientists and Researchers to translate complex requirements into robust, production-ready engineering solutions.
Qualifications
- Education: Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field; Master’s degree is a strong plus.
- Experience: 5+ years of professional experience in DevOps, SRE, or Machine Learning Infrastructure engineering.
- Technical Proficiency: Deep expertise in Python, Kubernetes, Docker, and Terraform.
- Cloud Mastery: Extensive experience with AWS, GCP, or Azure architecture and serverless computing.
- Problem Solving: Demonstrated ability to troubleshoot complex distributed systems and optimize performance under heavy load.