Résumé

Reina Kiperman, Leandro Emmanuel
Software developer

About me#

An avid self-taught backend software developer with great passion for "libre" software.

I love to work in a team where I need to be creative and resourceful, pushing me to grow both as a person and a professional.

Skills#

Programming

Python / Jupyter Java Bash / POSIX Shells Go / golang C / C++

Frameworks

JUnit / Mockito Spring / Spring Boot Pandas / NumPy Keras / TensorFlow

Electronics

Arduino Raspberry Pi KiCAD FPGA / VHDL

Tools

Git Nix Jenkins Kubernetes / Docker

Markup

reStructuredText MarkDown HTML LaTeX AsciiDoc

Data serialisation

JSON XML YAML

Operating Systems

Linux BSD MacOS Windows

Languages

English Spanish German

Experience#

OroraTech Embedded Linux Engineer 2021/11 — Present

I got an opportunity to move to Germany and work on a local startup, where I am currently in charge of creating and maintaining the full Linux software platform on a satellite. From the kernel and bootloader to the package management and update procedures, I am responsible that these mission critical components work flawlessly in orbit.

MuleSoft Software Engineer MTS 2020/08 — 2021/10

Right after I finished the previous project, the company started moving some of their most skilled employees into a new team with the purpose of developing an all new initiative: MuleSoft Composer. This is aimed at expanding our tooling for simpler tasks, broadening the possibilities for the non-technical users.

In this new endeavour, I had gone from leading a single of its core backend components to becoming one of the key players on the whole backend platform. From day one of the project I had helped with the analysis, design, and development of a microservices focused platform; driving the product all the way to GA and beyond.

MuleSoft Software Engineer AMTS 2019/02 — 2020/07

After the end of the Internship I was offered the opportunity to continue working at the company while I pursued my software engineering degree.

I took ownership of a project named MUnit Test recorder centred around simplifying our clients' development process, allowing to easily test and validate the correct functionality of their software, reducing time and effort. In order to achieve this goal, it was required to coordinate interactions across several teams to bring a smooth and cohesive experience to the end users.

By the end we saw 30% adoption increase and 25% usage compared to the old process within the first 3 months of the release of the new tool, and overwhelmingly positive feedback from our clientele.

MuleSoft Intern Software Engineer 2018/10 — 2019/01

I was part of the first "Colts" Internship after Salesforce acquisition, where I got the chance to work as a part of a core team (the MUnit team) and participate in a challenging project, giving me the fortuity to get hands-on experience.

Education#

Software Engineering Universidad Argentina de la Empresa 2018 — 2019

As time went by, I began to feel that I had been learning a lot more and in much more depth while working than I had ever done at the university, and finally resolved that it would be more beneficial to just keep polishing my skills on my job, and thus I decided to withdraw from college from the time being.

Electronic & Software Engineering Instituto Tecnológico de Buenos Aires 2013 — 2018

After diving into the Electronic courses I found that programming was what really motivates me, and so I opted to continue my studies as a software engineer. But because of my career change decision, I felt I needed to acquire some work experience. Although the tuition at ITBA was great, the timetables did not allow me to work, that is why I chose to continue at UADE.

Publications#

Simulation of pulse propagation in nonlinear optical fibres using GPUs 2016

We present an implementation in graphical processing units of a numerical algorithm for the simulation of the nonlinear propagation of pulses in optical fibres. The implementation uses NVidia's cuFFT library to perform the large number of FFTs calculations required and parallelises all vector sums and products. We show up to 50x speedups as compared to a single-core implementation on a PC.