About Scale
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 eval 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 head start among competition.
About Data Engine
At Scale, our Generative AI Data Engine powers 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.
About our Analytics Team
The Data Analytics team is responsible for centralized data, experimentation and reporting across all areas of Scale. We are building out the critical data pipelines, platforms and reporting, to support data-driven decision making and strategy for the company, including support for financial reporting, experimentations, and AI enabled insights.. The team are strong relationship builders and work in close collaboration with delivery, operations, finance, and engineering. You’ll be deeply invoiced in building flexible new systems to support experimentation across the company, and we are looking for engineers who are relentlessly curious and thrive on building systems from ambiguity.
Responsibilities:
- Provide critical input in the Data Engineering team’s roadmap and technical direction
- Deliver flexible and accurate experimentation systems.
- Work across backend and frontend systems
- Deliver at a high velocity and level of quality to engage our customers.
- Work across the entire product lifecycle from conceptualization through production
- Be able, and willing, to multi-task and learn new technologies quickly
- Work closely with cross-functional partners like finance, product, software engineers, and operations to identify opportunities for business impact, understand, refine and prioritize requirements for Data engineering.
Requirements:
- 5+ years of full-time engineering experience post-graduation, with specialties in production back-end services.
- Experience delivering products within the data engineering, data science and experimentation domains
- Experience developing and deploying software using industry-standard cloud-based tooling and frameworks.
- Experience scaling products at hyper-growth startups and excitement to work with AI technologies
- Strong written and verbal communication skills
- Strong problem-solving skills, and be able to work independently or as part of a team.
Nice to haves:
- Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
- Experience scaling products at hyper-growth startups.
- Excitement to work with AI technologies.
