Staff Software Engineer, Data Platform

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies. Provide technical leadership, including: upholding and upleveling engineering standards across the organization, mentoring junior engineers. Ideally you’d have: 8+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems. Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.). Show a track record of mentoring and leading teams in successful projects. Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders. Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings. Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems. Experience driving cross functional collaboration and communication at an organizational or broader level. Nice to haves: Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI). Experience with performance tuning and cost optimizations of cloud based data platforms. Experience defining a data lifecycle strategy and designing/implementing tooling for data privacy (i.e. GDPR) needs. Experience scaling products at hyper-growth startups. Excitement to work with AI technologies. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and addition