About Me
Thanks for visiting my website! Here you can learn more about my interests, experiences, and professional journey.
I am currently in a career transition, seeking challenging and fulfilling work where my skills can be fully utilized. Below, I highlight the skills I've gained throughout my career and my current goals.
Early Years and First Programming Experiences
I grew up in the East San Francisco Bay Area, in Contra Costa County. I attended UC Santa Barbara, where I obtained two bachelors of science degrees in Mathematics and Physics. Although these subjects were challenging and interesting, I found it difficult to envision a career deeply rooted in these fields. However, during my later college years, I took several programming classes through my majors and I found coding to be a highly stimulating and addictive activity, one where I could use my mathematical and problem-solving skills to build useful tools, or at the very least, clever doodads.
Data Science Club @ UCSB
In my second-to-last year, my friend convinced me to attend a Data Science Club meeting. I discovered a community of very talented and enthusiastic individuals who sought to combine coding with applied mathematics to create valuable tools and impressive projects. This was my first time realizing that data science would be a fascinating field to go into. I ended up joining the SpongeGuyParkFeld project, which involved a rather elaborate and open-ended analysis of the transcripts from the TV shows SpongeBob, Seinfeld, and South Park (Family "Guy" we did not end up analyzing but the name stuck!). Ultimately in conducting our analysis we all learned a lot about NLP and different machine learning and deep learning techniques to perform tasks like prediction and clustering. I was instrumental in helping give the project legs by scraping the transcript data from the internet, and defined a much more clear-cut task (classification) we could perform with this data. Showing we could achieve decent classification accuracy just from training some baseline ML models on our dataset prior to doing any real feature engineering gave the team confidence it could extract rich insights with deeper analysis techniques. This project was my first foray into data science, and it was a hit! Working with fellow aspiring engineers and data scientists was immensely rewarding and prepared me for my internship at FreeWire Technologies in 2018.
FreeWire Technologies
There I developed a touch screen user interface for their existing product line at that time. In that role I had to diligently listen to and learn from my teammates and mentors, and refine and adapt my software development skills. I learned more about what good code looked like by writing bad code and suffering the consequences, having to work off-the-clock to understand the mistakes I was making and how to fulfill my duties for the team, which culminated in a great final product that they could iterate on when my time was up.
FLIR
Then, in the next year following my internship, upon graduating from college, I began working for FLIR Systems (now Teledyne FLIR LLC) as a Software Engineer, where I learned even more valuable skills related to validating software, automating test cases, and designing software architecture. I learned how to build and publish my own Python packages, implement fixtures and plugins for our test automation framework, write sound unit tests, and quickly debug code, among many other things. Outside of really growing as a Python programmer, I gained exposure to the C programming language, learning the cameras' signal processing pipeline architecture, compiling and wrapping C SDKs to talk to the cameras, and successfully finding algorithmic bugs in their embedded software down to specific lines of code.
The Hunt for my Next Gig
After moving back to the Bay Area and working remotely for FLIR for about a year, my time at FLIR ended in 2023, and that prompted me to take a break from employment while I pursued different interests in order to identify my next career goal. After spending some months finding myself, I decided to delve more deeply into data science, specifically machine learning engineering, to see if I really enjoyed doing it and if it really made sense for me to commit to honing the skills required to transition into a professional career in that field. I enrolled in the UC San Diego Extended Studies MLE Bootcamp starting November 2023 and got to work. My pace started off slow on the introductory material, but as the assignments became more challenging and open-ended, I found myself getting very excited about trying out different machine learning architectures & APIs, feature engineering, model tuning and experimentation, deployment, and exploratory data analysis. The more hands-on I got with the curriculum, the more fun I was having, and my favorite part was working on my capstone project, LIRecommend, which I built to assist me in my job hunt, with recommending both jobs and skills I needed to prioritize gaining for those jobs. It is a tool that I designed for other people to be able to use as well, and I hope that they do! (If you're interested in trying the tool out for yourself, head over to the LIRecommend section for more info.)
At this point, since I'm still relatively new to the field of MLE, I will be happy to take the right job where I am critically involved in not only building but designing something of high value to the end user even if it's not MLE, however I am keen on this type of work and I am prioritizing roles or companies that involve it.