DatologyAI 内推 Solution Engineer 需符合岗位要求 2 YOE
DatologyAI Solution Engineer 岗位内推，要求 2 YOE，熟悉 ML 模型训练生命周期及 PyTorch，发帖人仅提供此岗位内推。
1. 关键信息
- (之前已归纳) DatologyAI 正在招聘 Solution Engineer，要求 2 年以上 AI/ML 技术或研究经验。
- (之前已归纳) 岗位薪资 OTE 范围为 $230K - $300K，薪资结构为 70/30 Base/Variable，并包含期权。
- (之前已归纳) 要求具备 ML 模型训练生命周期（pre-training, mid-training, post-training）的深入理解，以及 PyTorch 的实际操作能力。
- (之前已归纳) 熟悉大规模数据处理/分布式系统（Spark, Ray, data lakes/warehouses）者优先。
- (之前已归纳) 需要具备良好的沟通能力，能将复杂的 ML 和系统概念解释给不同受众。
- (之前已归纳) 强调需要有在快速增长的初创公司工作的经验。
- (之前已归纳) 避免主要动机是进行基础 ML 研究，以及有多个任职时间短于 1 年的经历。
- (之前已归纳) 岗位支持 Visa。
- (之前已归纳) 发帖人目前只能提供该特定 Solution Engineer 岗位的内推。
- 新增：有用户表示曾关注发帖人的视频内容，但认为其近期视频质量下降。
2. 羊毛/优惠信息
- 无
3. 最新动态
- 无
4. 争议或不同意见
- 新增：有用户对发帖人（疑似为某视频博主）近期视频内容质量表示不满。
5. 行动建议
- (之前已归纳) 符合岗位要求的网友可以联系发帖人获取内推机会。
- (之前已归纳) 如果用户对官网其他岗位感兴趣，发帖人目前无法提供内推。
这是我合作的recruiter推给我的 我自己比他的岗位senior了
说有适合的可以一起给他 最近找工难 如果网友适合也想跳槽换工作的话我就发给他
应该是DatologyAI公司recruiter那里看到的一手岗位要求 支持visa
Datology AI
DatologyAI: Train Better Models, Faster and Smaller
DatologyAI automatically curates model training data. Train faster, achieve better performance, and reduce costs with enterprise-grade data curation.
DatologyAI is a Series A company with over $57M in funding, backed by top-tier investors including Felicis, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, and Jeff Dean. They have developed a state-of-the-art data curation suite that automatically creates optimal training data for AI models.
This role offers a competitive OTE of $230K - $300K with a 70/30 Base/Variable split, plus equity. We are seeking candidates with 2+ years of experience and deep ML knowledge who are enthusiastic about the sales process.
Seniority
2+ years of experience in a technical or research role within the AI/ML space.
Work experience
Experience as an AI/ML Solutions Engineer, Researcher or Engineer.
Experience in a pre-sales or customer-facing technical role.
Experience at a fast-paced, high-growth startup.
Education
Master’s degree or PhD in a relevant technical field.
Hard skills
Deep understanding of ML model training lifecycles i.e. across pre-training, domain-specific mid-training and post-training.
Practical proficiency with PyTorch.
Experience with large-scale data processing / distributed systems (Spark, Ray, data lakes/warehouses).
Soft skills
Strong communication skills, with the ability to translate complex ML and systems topics for diverse audiences.
Miscellaneous
Willingness to travel to customer sites as needed.
Traits to avoid
Key motivation is conducting primary ML research.
Multiple short tenures (under 1 year) at previous roles.
你是nin11吧
nin是什么？
请问只有这个岗可以内推吗，还是官网的都可以呢
我目前只能推这个
我以前挺喜欢看这个up视频的，但这哥们去了洛杉矶后视频太水了