高级机器学习数据工程师
Senior ML Data Engineer
Intuition Machines 使用 AI/ML 构建企业安全产品。我们将研究成果应用于服务数亿人的系统，团队分布在全球各地。你可能已经了解我们最知名的产品——hCaptcha 安全套件。我们的方法很简单：低开销、小团队和快速迭代。
作为高级 ML 运维工程师，你将帮助设计和扩展支撑我们产品和研究工作的数据流水线。你将跨团队协作，设计、维护和改进高性能数据流水线，确保数据可访问、可靠且可扩展，以满足用户和内部利益相关者的需求。
使用 AI：代码代理无疑是很有用的工具。我们提供对前三大模型的访问，并是最早采用评估优先开发流程的公司之一。熟悉使用代理进行编码是所有面试的一部分。然而，可靠性与正确性对我们至关重要。你需要阅读并理解每行带有你名字的代码，并且代码将由人和机器共同审查。
你会做什么：
- 维护、扩展和改进现有的数据/ML 流程，并实现新的流程来处理高速数据。
- 提供接口和系统，使 ML 工程师和研究人员能够按需构建数据集。
- 影响数据存储和处理策略。
- 与 ML 团队以及前端和后端团队合作，构建我们的数据平台。
- 缩短仪表板和 ML 模型的部署时间。
- 建立最佳实践，开发流水线和软件，使 ML 工程师和研究人员能够高效地构建和使用数据集。
- 在性能约束类似于最大公司的条件下处理大型数据集。
- 快速迭代，注重尽早和频繁交付，确保新产品或功能可以部署给数百万用户。
我们寻找的人：
- 至少 3 年的数据相关工作经验，涉及设计和构建数据仓库、特征工程以及构建可处理高负载的可靠数据流水线。
- 至少 2 年在非数据工程岗位的专业软件开发经验。
- 精通 Python，并有使用 Kafka 基础设施和分布式数据系统的经验。
- 对 SQL 和 NoSQL 数据库有深入理解（优先考虑 Clickhouse）。
- 熟悉公有云供应商（AWS 或 Azure）。
- 有 CI/CD 和编排工具的经验
查看英文原文
Intuition Machines uses AI/ML to build enterprise security products. We apply our research to systems that serve hundreds of millions of people, with a team distributed around the world. You are probably familiar with our best-known product, the hCaptcha security suite. Our approach is simple: low overhead, small teams, and rapid iteration.
As a Senior ML Ops Engineer, you will help shape and expand the pipelines that power our products and research efforts. You’ll work across teams to design, maintain, and improve high-performance data pipelines, ensuring that data is accessible, reliable, and scalable to meet the needs of our users and internal stakeholders.
Using AI: Coding agents are indisputably useful tools. We provide access to the top 3 models, and were early adopters of evals-first development flows. Familiarity with coding using agents is part of all interviews. However, reliability and correctness are critical for us. You will need to read and understand every line of code with your name on it, and it will be reviewed by both people and machines.
What will you do:
- Maintain, extend, and improve existing data/ML workflows, and implement new ones to handle high-velocity data.
- Provide interfaces and systems that enable ML engineers and researchers to build datasets on demand.
- Influence data storage and processing strategies.
- Collaborate with the ML team, as well as frontend and backend teams, to build out our data platform.
- Reduce time-to-deployment for dashboards and ML models.
- Establish best practices and develop pipelines and software that enable ML engineers and researchers to efficiently build and use datasets.
- Work with large datasets under performance constraints comparable to those at the largest companies.
- Iterate quickly, with a focus on shipping early and often, ensuring that new products or features can be deployed to millions of users.
What we are looking for:
- Minimum of 3 years of experience in a data role involving designing and building data stores, feature engineering, and building reliable data pipelines that handle high loads.
- At least 2 years of professional software development experience in a role other than data engineering.
- Proficiency in Python and experience working with Kafka infrastructure and distributed data systems.
- Deep understanding of SQL and NoSQL databases (preferably Clickhouse).
- Familiarity with public cloud providers (AWS or Azure).
- Experience with CI/CD and orchestration platforms: Kubernetes, containerization, and microservice design.
- Proven ability to make independent decisions regarding data processing strategy and architecture.
- Thoughtful, self-directed individual who is able to operate effectively in a fast-paced environment.
Nice to Have:
- Experience collaborating across ML, backend, and frontend teams.
- Understanding of machine learning fundamentals, including model training, inference, and frameworks such as PyTorch or TensorFlow.
What we offer:
- Fully remote position with flexible working hours.
- An inspiring team of colleagues spread all over the world.
- Pleasant, modern development and deployment workflows: ship early, ship often.
- High impact: lots of users, happy customers, high growth, and cutting-edge R&D.
- Flat organization, direct interaction with customer teams.
We celebrate equality of opportunity and are committed to creating an inclusive environment for all team members. Join us as we transform cybersecurity, user privacy, and machine learning online!
Please note that all positions require pre-employment screening, including third-party verification of work history, education, and identity, as well as a final in-person interview and identity verification step, which will be conducted in your country of residence.
Originally posted on Himalayas