Luis Redondo
Cañada

In this new role, my main focus has been leading the revamp of the internal Machine Learning Infrastructure, by:

• Gathering feedback from the Data Science team, our primary users, to identify key pain points and limitations of the current platform.
• Conducting a state-of-the-art analysis, evaluating available platforms and products to determine the best foundation for our solution.
• Running multiple proof-of-concept projects to test and validate different components of the final architecture.
• Leading the development phase, spearheading the adoption of KServe along with technologies like Istio and Knative.

As a member of the technical team, played a vital role in managing and advancing our company's Data Infrastructure, mostly hosted on Google Cloud Platform. My contributions include:

• Architecting and maintaining robust DataLake (GCS) and DataWarehouse (BigQuery) pipelines using Scala and Apache Beam, handling around 10ks event per second and processing about a 1TB of data daily.
• Developing and optimising a suite of Go-based ETLs, which has streamlined the integration of third-party data into our DataWarehouse.
• Spearheading the overhaul of our Python-centric machine learning platform, that aims to reduce time to market for Data Science models. Also acted as ML Ops, ensuring the smooth functioning of the almost twenty live models.
• Managing our cloud with Terraform, maintaining Kubernetes clusters, implementing automated deployments via ArgoCD, and keep a close on our cloud costs (haven't grown since joining the team, despite Cabify quadrupling its volume).

My tenure is marked by a desire to expand my technical knowledge in a new field. Having been able to expand from a smaller role, to now lead data-centric initiatives, has been very rewarding.

In my stint as Engineering Manager, had two different roles:

• Tech lead for the Android Driver team: establishing our technical roadmap, prioritizing developments and growing the team.
• Engineering manager of a team of backend, frontend and mobile developers in one of the teams inside Driver.

Both roles required to work closely with product management, to align the business roadmap with the technical roadmap, to ensure that we could keep up with upcoming requirements.

A constant during this time was the need to connect people inside Cabify, in and out of my team, to collaborate on wider projects. This allowed to succeed in some projects while promoting autonomy inside the team.

One of most satisfying parts of this role was to help colleagues develop their careers at Cabify, while pushing forward our business.

Joined Cabify to be part of the Android team, which develops both Android apps that Cabify offers (passengers and drivers).

Kickstarted the rewrite of the Driver application, since it was riddled by technical debt. The main blocks of the new architecture are still in place, and it has supported the Cabify's growth since its publication, going from pure Java to Kotlin gradually.

Worked briefly on the hybrid version of the Rider app (Cordova), improving its native experience by developing native plugins. After we decided to start the Rider app from scratch, in Kotlin, also helped on putting the architecture foundations, heavily based on RxJava.

The Driver app is the work tool of our drivers, so our main focus is stability and reliability, while offering an experience tailored to be used while driving. It makes intensive use or GPS sensors, background activity and map interactions.

Worked as a mobile developer, primarily on Android while assisting with iOS. Developed multiple Android apps for live election coverage in Argentina, El Salvador, Colombia, the EU Parliament, and local Spanish elections.