AI Infrastructure Engineer, ML Data Platform

Job Description

Scale is seeking a Data Infrastructure Engineer to join its AI Infrastructure team. This team supports both R&D and applied Generative AI initiatives, driving breakthroughs in areas of post-training research. The Data Infrastructure Engineer will design, build, and scale the data platform that powers all R&D and applied ML initiatives at Scale. He/She will collaborate closely with product engineering, platform engineering, and ML researchers to build robust and easy-to-use APIs and data pipelines. The engineer's work will play a critical role in advancing frontier ML research, accelerating the data sales cycle, and improving data quality - all while optimizing infrastructure costs.

Role involves:

• Designing, implementing, and maintaining scalable data platforms to support diverse R&D and applied ML workloads.
• Partnering with ML researchers, product engineers, and operations teams to align data infrastructure with organizational goals.
• Collaborating with ML researchers to build data access tools that help advance the state of frontier post-training research.
• Participating in our team’s on call process to ensure the availability of our services.
• Owning projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Requirements:

• 2+ years of experience in building and operating large-scale distributed data systems that support ML workloads.
• Expertise in modern data platform technologies.
• Experience working with standard containerization & deployment technologies like Kubernetes, Helm, Terraform, Docker, etc.
• Strong problem solving skills and the ability to work effectively in a fast paced, dynamic environment.

Role offers:

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO