As a fast-growing deep tech startup, our mission is to unlock the true potential of generative AI for startups, enterprises, and the public sector. Our research-driven platform provides customers with the tools to develop custom AI models designed to meet their specific needs, leveraging high-quality data and adhering to the highest standards of data privacy.
Details about the role
As ML Infrastructure Engineer you’ll be part of building the next-generation AI training platforms. You will architect and implement the infrastructure that powers our large-scale language and vision model training operations, working across bare metal GPU clusters and cloud environments. You’ll be at the intersection of high-performance computing and modern DevOps, designing automated solutions for cluster deployment, optimization, and management. This is a unique opportunity to tackle complex challenges in distributed systems while working with cutting-edge AI technologies. You’ll play a crucial role in developing the infrastructure that enables our ML teams to efficiently train and deploy large-scale models, from designing high-performance GPU clusters to implementing sophisticated orchestration systems for distributed training workloads.
Responsibilities
Design and implement scalable infrastructure for large GPU clusters Develop and maintain automated deployment systems for standing up GPU clusters Create and maintain Infrastructure as Code (IaC) templates Design and implement job scheduling and workload management systems Collaborate with ML engineers to optimize training infrastructure Develop automation tools and scripts for cluster management Implement security best practices and compliance measures Requirements: Strong expertise in Infrastructure as Code tools Proven experience with container orchestration platforms Deep understanding of networking concepts Experience with CI/CD tools and practices Proficiency in infrastructure automation programming languages Demonstrated experience with GPU computing and technologies Benefits: Opportunity to work in a fast-growing startup environment Competitive salary & equity compensation Networking opportunities within the industry Remote work from anywhere Flexible working hours Rapid career growth opportunities A Final Note You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.