应用数学专员 - 全远程 | 最高100美元/小时
Applied Mathematics Specialist - Fully Remote | Upto $100/hr
关于职位
Mercor 将顶尖的创意和技术人才与领先的 AI 研究实验室联系起来。公司总部位于旧金山，我们的投资人包括 Benchmark、General Catalyst、Peter Thiel、Adam D'Angelo、Larry Summers 和 Jack Dorsey。
职位：计算贝叶斯统计与应用数学专家
类型：合同工
薪酬：70–100 美元/小时
地点：远程
投入：每周 15–20 小时
岗位职责
- 设计具有挑战性的计算问题，以测试 AI 在解决科学和工程任务方面的能力。
- 开发需要使用专业科学软件进行模拟和实验设计的问题。
- 通过与最先进 AI 模型的迭代测试来优化问题难度。
- 协作创建需要战略思维和高效信息提取的任务。
- 独立工作，根据反馈和模型表现改进问题设计。
资格要求
必备条件
- 相关 STEM 领域的研究生水平培训（硕士、博士或同等研究经验）。
- 至少掌握一个科学软件库（如 PyMC、FEniCS 等）的熟练技能。
- 强大的 Python 技能，用于编写问题设置和解决方案验证器。
- 能够独立工作并优化问题设计。
- 熟悉 Linux/终端环境和远程计算沙箱。
- 每周至少有 15–20 小时可用时间。
优先考虑
- 在多个领域或工具方面有经验。
- 熟悉基准测试或评估设计。
- 有科学教学或考试/题集设计背景。
- 具备计算可重复性和容器化环境的经验。
申请流程（需 20–30 分钟完成）
- 上传简历
- 基于简历的 AI 面试
- 提交表单
资源与支持
- 有关面试流程和平台信息的详细内容，请查看：
- 如有任何帮助或支持，请联系：
备注：我们团队每天都会审核申请。请完成 AI 面试和申请步骤，以便考虑此机会。
最初发布于 喜马拉雅山
查看英文原文
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Computational Bayesian Statistics and Applied Mathematics Expert
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
- Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.
- Develop problems requiring the use of specialized scientific software for simulations and experiment design.
- Refine problems through iterative testing against state-of-the-art AI models to achieve target difficulty.
- Collaborate on creating tasks that require strategic thinking and efficient information extraction.
- Work independently to enhance problem designs based on feedback and model performance.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- Proven proficiency with at least one scientific software library (PyMC, FEniCS, etc.).
- Strong Python skills for writing problem setups and solution validators.
- Ability to work independently and refine problem designs.
- Comfortable in a Linux/terminal environment with remote compute sandboxes.
- Available for at least 15–20 hours/week.
Preferred
- Experience across multiple domains or tools.
- Familiarity with benchmark or evaluation design.
- Background in scientific teaching or exam/problem-set design.
- Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check:
- For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas