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Scale is building the Generative AI Data Engine and related products that power the world's most advanced LLMs through RLHF, human data generation, model evaluation, safety, and alignment. The Platform Engineering team is seeking a Senior Software Engineer to design and develop shared foundational platforms used across Scale's infrastructure.
In this role, you will drive the design and implementation of foundational data platforms and lifecycle management, architect Scale's core cloud infrastructure and orchestration stack, and redefine how engineers develop, build, test, and deploy software. You'll collaborate cross-functionally to define requirements and deliver features in an iterative, innovative development environment. You'll also gain exposure to the forefront of the AI race as Scale works with enterprises, startups, governments, and large tech companies.
Key responsibilities include: designing and implementing foundational platforms and systems that become the baseline for Scale's capabilities; collaborating with cross-functional teams to understand requirements and deliver new features; leading market innovation in your domain through experimentation with latest techniques; identifying and driving improvements to programming practices, processes, and tools; and presenting technical information to teams and stakeholders.
Required qualifications: 5+ years of full-time post-graduation engineering experience with back-end systems specialization; deep understanding of highly scalable and reliable distributed systems on public cloud platforms; strong track record of independently owning and delivering successful engineering projects; excellent communication and collaboration skills; fluency with containerization and deployment technologies (Kubernetes, Terraform, Docker); experience with agent/code orchestration platforms like Temporal; mastery of structured databases including Postgres; strong knowledge of software engineering best practices and CI/CD tooling.
Desirable experience includes: building document retrieval and understanding systems (RAG); multiple cloud platforms (GCP, AWS, Azure, Oracle); knowledge graphs and hierarchical indexes; large data solutions (Databricks, Snowflake); authentication/authorization systems; scaling technical products at hyper-growth startups.
