OpenAI3 дня назад
Инженер-программист, обучение в продуктах OpenAI
Зарплата не указана
РЫНОК
16 250 ₽медиана по профессии
Data Scientist · 212 вакансий с указанной зарплатой
5 000половина предложений: 13 084–21 768120 000
Работодатель не указал зарплату — сравните с рынком сами.
Полная занятостьУдалёнка
Обязанности
- 01Own the vision and execution for OAI’s native learning offering
- 02Build and launch end-to-end product experiences that help users build and apply AI skills through real work, starting in ChatGPT
- 03Design the core systems behind those experiences, including learner state, progress and re-entry, content and runtime integration, experimentation, telemetry, and evaluation
- 04Create reusable components and internal tools that allow education and content partners to develop, configure, test, and improve learning experiences
- 05Build and test clear entry points, realistic hands-on practice, useful feedback, telemetry, and evaluation
- 06Partner closely with colleagues across Customer Readiness, EDU Engineering, learning science, research, design, data, content, support, and customer-facing teams
- 07Work closely with design and users to turn product and learning goals into clear requirements, prototypes, milestones, reusable UI patterns, and product metrics
- 08Define the learner intent and problem for each release, then use product data, learner feedback, and operational signals to evaluate product quality
- 09Make pragmatic tradeoffs across speed, quality, scalability, and operational simplicity in a 0-to-1 product area
Требования
- 01Substantial experience building and operating high-quality user-facing products with a record of staff-level technical leadership and hands-on delivery
- 02Strong full-stack engineering skills, including modern frontend technologies such as TypeScript and React, backend services and APIs, relational databases, stateful user flows, and instrumentation
- 03Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success measures are still evolving
- 04Strong user empathy and a high bar for product and interaction quality, accessibility, reliability, safety, security, and performance
- 05Experience collaborating across engineering, research, product, design, data, content, operations, and customer-facing teams
- 06Ability to use qualitative feedback and product data to identify friction, prioritize work, and improve outcomes
- 07Clear written and verbal communication, including the ability to explain technical decisions and tradeoffs to different audiences
- 08Careful judgment when building products that shape how people understand and use AI