Job Description
We are pioneering the infrastructure required for the next generation of artificial intelligence. As we look toward 2026, our engineering team is seeking a visionary Senior AI Infrastructure Engineer to architect scalable, high-performance systems that power our cutting-edge generative models.
In this role, you will bridge the gap between machine learning research and robust production deployment. You will design the data pipelines that train the models of tomorrow, ensuring they are not only fast but also energy-efficient and sustainable. If you are passionate about the intersection of cloud computing, deep learning, and future tech trends, we want to meet you.
Why Join Us?
We offer a competitive compensation package, equity opportunities, and the chance to work on projects that define the future of technology.
Responsibilities
- Architect and manage large-scale Kubernetes clusters dedicated to AI training and inference.
- Optimize GPU utilization and model serving latency to handle millions of concurrent requests.
- Implement advanced CI/CD pipelines for machine learning models, ensuring rapid iteration and deployment.
- Collaborate with data scientists to translate research prototypes into production-ready microservices.
- Ensure system scalability, fault tolerance, and security in multi-cloud environments.
- Drive initiatives to reduce the carbon footprint of our compute infrastructure.
Qualifications
- 5+ years of experience in software engineering, DevOps, or infrastructure.
- Deep expertise in Python, Go, or Rust, and familiarity with ML frameworks (PyTorch, TensorFlow).
- Proven experience managing Kubernetes, Docker, and cloud platforms (AWS, GCP, or Azure).
- Strong understanding of distributed systems, message queues, and high-availability architectures.
- Experience with Kubernetes Operator patterns and serverless computing.
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.