机器学习工程师

您将负责什么

• Take speech and language models from evaluation into production, including the serving path and what it costs to run.
• Build evaluation sets that reflect the languages and accents customers actually speak, not the ones a public benchmark ships with.
• Instrument models in production: drift, latency, and the failure cases customers report.
• Work with the platform team on the data path, so that training data stays in the jurisdiction the customer requires.
• Document model behaviour and its limits to a standard a regulator can read.

您需要具备什么

• You have deployed models to production and maintained them afterwards, not only trained them.
• You are comfortable with PyTorch or an equivalent framework, and with the serving stack around it.
• You understand speech or natural language processing well enough to know where the benchmarks mislead.
• You treat privacy and data residency as engineering constraints rather than as paperwork.
• You work in English. Other languages spoken in the group’s markets are an advantage.

五个步骤，每一步您都清楚自己所处的位置

1. 1投递申请您通过本网站投递申请。阅读它的是一个人——第一道筛选并非由系统自动完成。
2. 2初次沟通与用人经理通话，谈的是工作本身：您做过什么、运营过什么，以及这个职位真正需要什么。
3. 3实务案例一道取自真实系统的题目，工作量控制在一次合理的时长之内。我们会与您当面讨论，绝不在您不知情的情况下打分。
4. 4小组面试您将见到未来共事的同事，以及一位来自团队之外的同事——他的职责就是提出那个不好回答的问题。
5. 5最终决定录用与否，都会给出理由。无论结果如何我们都会告知您，并会事先说明何时告知。