Machine Learning Engineer

Florianópolis, Santa Catarina, Brasil Full-time

Hello there! We are a multidisciplinary team of Data Scientists and Engineers looking for our next office buddy. So if you think you got what it takes to come up with performant algorithms that will serve recommendations for some of the biggest e-commerces in Latin America: buckle up for the journey.

The types of problems you'll solve are both deep and diverse, for this you will need a strong background in data structures and algorithms since a big part of this job is processing terabytes of data. In scenarios like these, the choices you make can greatly impact performance. Not only that but you need to be a good architect as well, being able to elaborate real-time algorithms if needed, that run under strict latency conditions, for example.

In our team, we mostly use Python which, like most dynamic languages, is not very forgiving of bad abstractions. So your coding fluency needs to be a good fit. We also value knowledge of shell scripting, as well as past experience with frameworks like Dask, Spark (via PySpark), SciKit-Learn, and TensorFlow. Regarding infrastructure, we run on top of AWS. Past experiences using EC2/S3/others, as well as vendor-agnostic technologies like Kafka or Elasticsearch count for bonus points.

As a member of the Data Science Team, your domain-specific knowledge needs to be on point: A good grasp on statistics, a skeptic mindset, as well as understanding the sociometric insights of the datasets you work with is an absolute must. A deep understanding of linear algebra and mathematics in general will earn you high praise amongst your peers. Having some experience with the inner workings and techniques that empower other search/recommendation systems will earn you a ton of bonus points.

All in all, the highest evaluation criteria is your potential and showing that you can do good things for the team, so that we can build great things together. But since we kinda have to add bullet points to these things, here's a recap:

  • Good knowledge of Data Structures, Algorithms, and Systems Architecture;
  • Concrete understanding of Data Sciency fields of math (LinAlg, Calc, Stats, etc);
  • Fluency in Python, or the ability to become fluent in a relatively short time;
  • Having good experience with programming and knowing how to abstract properly is great to have;
  • Bonus points for having worked with Dask, Spark, SKLearn, TensorFlow, or the ELK stack;
  • Bonus points if you can link us to cool stuff you did on Kaggle/GitHub;
  • Super bonus points for having worked with recommendation systems or search engines before.

Did you like it? Come build great things with us =]