Hi there!

One of the pleasures of my frequent travel is the opportunity to meet with TWiML listeners at conferences and in their home cities. During one such informal meetup last year I sat at a sidewalk cafe in Toronto sipping a coffee and chatting with a listener about his search for his next data science job. As we talked it occurred to me that many of the listeners I’ve met with have mentioned either looking for their next gig or recently switching jobs. Apparently, this isn’t just the folks I hang out with; a recent survey showed that nearly a quarter of data scientists changed jobs in 2017!

I realized at that point that TWiML could provide a valuable resource to members of the community by connecting them with high-quality career opportunities, and the creation of a TWiML job board was added to our to-do list. Why yet another job board? That’s a really good question. There are a ton of job boards, so what would be different about a TWiML job board? Well, first of all, most of them suck and we think we can do better. 

Here are some of the worst problems with current job boards:

  1. Shadow jobs. It turns out that a lot of the jobs on job boards don’t actually exist. They’re scraped by aggregators with no relation to the hiring companies, maybe months ago, to create the illusion of breadth and drive SEO traffic. Or, maybe they're posted to collect resumes for future use. They’re rarely vetted for existence or quality.
  2. Black-hat tactics. Unscrupulous agency recruiters have a bad reputation among technical professionals. Part of the reason is the use of “black hat” techniques like misleading job descriptions or bait-and-switch tactics that frustrate job seekers, waste their time, and lead them on.
  3. Poor differentiation. Too often listings feel generic, not offering enough detail to help the job seeker understand the role or the hiring organization, or differentiate it from other positions or companies.

By posting only quality posts by vetted hiring organizations, we'll eliminate the worst of these problems. We’ll work with hiring companies to create better listings and we’ll continue to innovate over time to improve the way our community members gain access to the best ML and AI jobs. We're excited about the opportunity to help the TWiML community advance their careers.

Right now we’re reaching out to hiring organizations to identify our first set of partners. If you’re a hiring manager or inside recruiter and you’re looking hire some of the best ML and AI talent in the industry, hit reply and let’s talk. And if you’re actively or passively job hunting, I’d also love to hear from you on what you’re looking for and how we might help.



New On the Pod

Both of last week's pods are among my all-time favorites. Be sure to check them out!


Bits & Bytes

  • DeepMind AI needs just a few images to construct a 3D model. Google DeepMind has developed Generative Query Network, a new algorithm that can render simple 3-dimensional scenes from static images.
  • Amazon ships DeepLens; adds support for TensorFlow and Caffe: AWS DeepLens is now shipping to a developer near you. The company has added some new capabilities, including TensorFlow and Caffe support. DeepLens also now supports the Deconvolution, L2Normalization, and LRN layers provided by MXNet.
  • Oracle advances AI effort to automate DevOps: Oracle announced the availability of its new Oracle Cloud Platform services which touts new AI and machine learning capabilities. The new platform aims to automate operational, security, and recovery tasks for cloud users.

Dollars & Sense



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