Act like a leader

 

I spent the past few days binge reading the book “Act Like a Leader, Think Like a Leader” by Herminia Ibarra. I rarely read books on leadership, partly because I identify myself first as an IC (individual contributor) and a tech expert, not a leader, a role I consider as more talking than working, and partly because I always think it is a waste of time to think about leadership when I’m not even a leader. I’d rather spend more time pushing my code to production and delivering a solution. This book completely changes my naive perception of how leadership develops and motivates me to act now.

【职场分享】如何让自己有话可说 / How to be a good verbal communicator at work

工作之后,我渐渐发现自己一个人干活的时间越来越少,而跟人说话的时间越来越多。跟人说话,包括组里的工作会议,比如daily standup、spring planning、pairing、demo,跟老板和组里同事的日常1on1,跟越级老板的1on1,跟其他相关stakeholder的开会扯皮,茶水间的闲聊,等等。一开始我很不适应,因为我更习惯asynchronous的方式,有足够的时间思考说什么,琢磨一句话要怎么表达。我以前觉得,有什么话不能在slack上说,不能发一封邮件,不能在google doc上留言呢。但现在的我:synchronous真香,面对面才是王道。

【职场分享】程序员如何出活 / How to deliver fast as an IC

从entry level升到senior的路径通常很清晰,从技术上讲,就是能deliver能出活。从一个小ticket开始做,到独立完成一个feature相关的若干ticket,再到独立完成若干个feature的时候,基本就是senior的水平了。其他方面的衡量标准(主要是soft skills)以后单独聊。

【职场分享】新人如何打基础 / How to lay the foundation for a new job

在科技公司工作四年半,我从一个新人成长为一个资深工程师,一路上有很多贵人相助,我自己也带了不少新人。有一些工作的感想,会在接下来的几篇博客里跟大家分享一下。下面是第一篇,新人如何打基础。

Senior engineer and then what?

This March, I got promoted to a senior machine learning engineer. Stepping into this new role, I thought I was more than prepared. After all, people only get promoted to the next level after they already function like the next level. Now, I have worked as a senior engineer for half a year, and I gradually realize that while the daily technical work may appear similar for a senior engineer, being a senior engineer opens many doors and prompts me to think what I truly want for my career. 

Onboarding as a Machine Learning Engineer

It’s been 3 months since I started my new position as a Machine Learning Engineer (MLE) at Spotify. What I like most about this position is that I get to participate in building an end-to-end pipeline, including ideation and experiment, data engineering, machine learning modeling, model serving, online A/B test, monitoring, and many more.