Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to architect the backbone of our next-generation artificial intelligence platform designed for the 2026 era. In this role, you will bridge the gap between cutting-edge research and scalable production systems. You will be responsible for deploying high-performance computing clusters that handle petabytes of data and training the most advanced neural networks available today.
At FutureScale Technologies, we don't just predict the future; we build it. Join a team of elite engineers dedicated to solving the most complex infrastructure challenges in Machine Learning and Quantum Readiness.
What You Will Do
Responsibilities
- Architect and maintain scalable distributed training clusters for large language models.
- Optimize model inference latency and throughput using edge computing strategies.
- Implement robust MLOps pipelines to automate model training, validation, and deployment.
- Collaborate with data scientists to translate complex research papers into production-grade code.
- Ensure system resilience, security, and compliance with 2026 data privacy standards.
- Lead technical design reviews and mentor junior engineers in best practices.
Qualifications
- 5+ years of professional experience in Backend Engineering, DevOps, or Systems Architecture.
- Strong proficiency in Python, Go, or Rust.
- Extensive experience with Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
- Deep understanding of Machine Learning concepts, neural networks, and MLOps.
- Experience with hardware acceleration (GPUs/TPUs) and high-performance computing.
- Bachelor’s degree in Computer Science, Engineering, or related technical field.