高级机器学习应用科学家
Senior ML Applied Scientist
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，团队成员分布在世界各地。你可能已经了解我们最知名的产品——hCaptcha 安全套件。我们的方法简单：低开销、小团队和快速迭代。
作为 ML 应用科学家，你将设计、实现并扩展支持我们产品的机器学习系统。你将跨团队协作，将业务目标转化为技术规范，确保我们的模型在现实约束下高效运行。该职位结合了研究、工程和指导，在快节奏的生产环境中工作。
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。熟悉使用代理编写代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你署名的代码，并且它将由人和机器共同审查。
你将负责：
- 构建可扩展至每秒数百万请求的 ML 模型，同时保持性能。
- 将业务需求转化为技术规范。
- 开发满足内存和计算限制的 ML 模型，进行正确评估并有效调试。
- 为其他 ML 研究工程师提供技术指导。
- 快速迭代，注重尽早并频繁交付，确保新产品或功能能部署给数百万用户。
- 编写结构清晰、可维护、文档齐全且经过测试的代码，包括单元测试、集成测试和端到端测试。
- 参与代码审查和架构与设计会议。关注最新的技术发展并评估其适用性。
- 为研究路线图提供技术建议。
我们寻找：
- 5 年以上应用 ML 相关的实践经验。
- 在整个建模生命周期中有实际经验：构建、评估和调试大型 ML 模型。
- 具有大规模分类和结构化数据的经验。
- 在实时 ML 模型、增量学习和在线学习方面有专长。
- 对 ML 基础知识有深刻理解：偏差-方差权衡、损失函数、评估指标等。
- 技术领域的学士学位（或同等实践经验）。
- 思考周全、自我驱动
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 an ML Applied Scientist, you will design, implement, and scale machine learning systems that power our products. You’ll work across teams to translate business goals into technical specifications, ensuring our models perform efficiently under real-world constraints. This role combines research, engineering, and mentorship in a fast-paced production environment.
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 you will do:
- Build ML models that can scale to millions of requests per second while maintaining performance.
- Translate business requirements into technical specifications.
- Develop ML models that satisfy memory and compute constraints, evaluate them properly, and debug effectively.
- Provide technical mentorship to other ML research engineers.
- Iterate quickly, with a focus on shipping early and often, ensuring that new products or features can be deployed to millions of users.
- Write clearly structured, maintainable, well-documented, and tested code, including unit, integration, and end-to-end tests.
- Participate in code reviews and architecture & design sessions. Stay updated on recent technological developments and assess their applicability.
- Provide technical input to the research roadmap.
What we are looking for:
- 5+ years of professional experience in applied ML.
- Proven experience with the entire modeling lifecycle: building, evaluating, and debugging large ML models.
- Experience with large-scale categorical and structured data.
- Expertise in real-time ML models, incremental learning, and online learning.
- Strong understanding of ML fundamentals: bias-variance tradeoffs, loss functions, evaluation metrics, etc.
- Bachelor’s degree in a technical field (or equivalent practical experience).
- Thoughtful, self-directed individual who is comfortable making technical decisions independently.
Nice to Have:
- Strong grasp of the math required for ML (linear algebra, probability theory, statistics, matrix calculus).
- Software engineering/development experience with large-scale distributed systems.
- Ability to collaborate with ML engineers to integrate your work into our infrastructure, including automating observability, deployment, quality, and security.
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