Are you a robot? You're hired. If not then could you build a robot for us please. If not then how about understanding and working with data? If I mention the word Big Data, did you just throw-up a bit in your mouth? Good, then we want you. Big Data. Sorry, I won’t mention it again. Can you wade through all the hype and buzz words of Machine Learning and just actually understand what it takes to do intelligent things with any amounts of data? Good, then we want you.

You will design and implement machine learning across our clue processing pipeline including object classification, language processing, and localization. You will work within the software team to solve the many hard problems we have to overcome. If this challenge excites you, we’d love to hear from you.

Entry Level

(We will start to read the email and then potentially laugh. I will then call one of the other guys over and we will laugh together…for an hour)

• You have installed MatLab.
  
• You have uploaded a picture of a cat to an image recognition site and when it said it was a cat it blew your mind.

Some Interest

(I openly make the sound “Hmmpf”. We will read the full email)

• You have used Matlab, R, Python or really any language to run algorithms over any data.
  
• You have installed RServer, Spark, Mahout and have samples of code you have written against these frameworks.
• You know what Tokenisation is and you know off the top of your head what Lemmatisation, Stemming and Fuzzy Matching is without looking at Google. Did you just go to Google? Then you failed.

Interested

(I will pick up Seymour, the office dog, and stroke it like in a bond film and we will respond to the email with an online interview.)

• You know the difference between different hashing algorithms and when to use which ones.
• You know how to build data models to be used in Supervised Learning, Random Forest, SVM, K-Means or Bayesian Algorithms and when you would use which algorithm on different data..
• You have experience in Bag of Words, Fuzzy Matching, Feature Extraction.
• You know how to do Topic Extraction, Clustering, Pattern Detection and more.

Very Interested

(I will legally change my name to a name of your choice and we will sign anything you want, for anything you want.)

• You are a contributor to popular text analysis or mathematics libraries such as Stanford NLP, Serf.
  
• You have built your own hashing algorithms.
• You have built your own fuzzy matching libraries.
• You have built your own inference engine.
• You are Andrew Ng.
• You are a robot.

If you want to get past the buzz words of Machine Learning and actually build some practical applications, then send your favourite joke and let's meet up.