Software Engineer, ML Data Systems

Навыки

• ClickHouse
• Dagster / Prefect / Luigi
• Дашборды и витрины
• Databricks
• dbt
• Отладка и поиск ошибок
• Machine Learning

О компании и продукте

• Cursor ships daily. Every release leaves signals behind: telemetry, prompts, completions, agent runs, sessions. Those signals power model improvement, evals, and experimentation. Data infrastructure is what turns them into something teams can trust.
• A lot of systems here started simple so we could move fast. Over time, the constraints change and the “good enough” version becomes the bottleneck. This role owns the full ladder: patch what should be patched, redesign what should be redesigned, ship the replacement, and operate it.
• Privacy guarantees are part of correctness. What we can retain and use depends on Privacy Mode and org configuration, and getting that wrong breaks a product promise. We choose work by business impact: what blocks product and model teams today, and what will block them next month.
• A core pipeline started as a pragmatic reuse of infrastructure built for something else. It works, but it cannot guarantee properties downstream consumers now need (for example, point-in-time consistency). You design and ship the replacement while keeping the existing system running.

Требования

• We’re looking for someone who has built real systems at scale and cares about correctness, cost, and ergonomics
• Strong signals include
• Deep experience with Spark (Databricks or open-source Spark both count)
• Production experience with Ray Data
• Hands-on ownership of large data pipelines and storage systems
• Comfort debugging performance issues across client instrumentation, streaming, storage, and model-facing workflows, as well as, compute, storage, and networking layers
• Clear thinking about data modeling and long-term maintainability
• You have good judgment about when to patch and when to rebuild

Будет плюсом

• Experience running or scaling ClickHouse
• Familiarity with dbt, Dagster, or similar orchestration and modeling tools
• We're in-person with cozy offices in North Beach, San Francisco and Manhattan, New York, replete with well-stocked libraries
• APPLYING
• If there appears to be a fit, we'll reach to schedule 2-3 short technicals
• After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team

Паспорт вакансии

История публикации

Откуда что взялось

Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.

Почему на этом месте в выдаче

Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.