I’m not a religious person. I don’t know if I consider myself spiritual, but I’ve had too many coincidences in my life that have worked out in my favour not to give some credence to the universe ushering me along a path it wants me to follow. I feel like this entire year has been a lesson in the universe asking me to put faith in what it has in store for me, given the disruptions that have occurred. From the ending of a relationship/situationship I wanted to be a forever thing in January, to my ex-husband relocating to Australia, impacting the amount of time I have with my children and decisions I have to make as a result, to the team I had been working with for the last three years, including myself, being impacted by layoffs back in August.
I think a common immediate reaction to being laid off is a bout of depression, fear, anxiety, and maybe a loss of a sense of self. I, surprisingly, didn’t feel any of these things. I don’t know if that’s because of autistic processing time, or because I have a genuine belief in my abilities now that I’m so sure that things will work out for me, whatever happens. This job I was let go from, along with my previous job as a tour guide, fell into my lap and were exactly what I needed, right when I needed them. I’ve got a detailed enough LinkedIn profile that recruiters reach out to me every now and then so that I haven’t felt like I needed to look very hard to find something new.
But I’ll explain a little why I feel confident I’ll find a new role by highlighting some of my many accomplishments in the last three years, that I’m proud of.
Initially I was hired as a part-time Curriculum Engineer, working on improving the Data Analytics boot camp I took through UC Berkeley Extension from August 2020-February 2021. My first project involved changing out a number of datasets in the curriculum and replacing them with new ones. I think I replaced over 60 datasets, and made improvements to the curriculum as I went. Then, I converted that curriculum for an Australian audience, swapping out American-centred datasets for Australian, other countries or more universal ones. As an Australian myself, as part of that process, I also converted all the US English to Australian English. Given how time consuming that process was, I wound up having the opportunity to write a Python script to automate the process of changing the language, which I later converted to a Flask app that you could run from a Docker container. I had zero experience with Docker before this task, so I really appreciated the opportunity to learn a new technology whilst also advancing my Python skills. I later repurposed some of the code from that original script to automate other processes when we had curriculum updates.
When my team was tasked with updating the Data Analytics curriculum to introduce some new topics, and expand on others, I was assigned the module on NoSQL databases, specifically using MongoDB. As a bit of a database nerd, I loved getting to develop this content. The previous version of the curriculum only had about a day of content on MongoDB, and I expanded it into three days. That meant I couldn’t just repurpose existing content – I got to dive into the MongoDB documentation and decide what might be most useful for students to learn. I taught them how to write queries in their Terminal with Mongo Shell, as well as how to use PyMongo to write Python code for their queries.
During the next major project I worked on, I was promoted to a full-time position. That next project was an 8-week AI and Machine Learning microbootcamp, targeted at audiences who already knew how to code in Python, they just wanted to advance their skills to include machine learning. The company wanted to jump on the popularity AI was getting thanks to ChatGPT. I was assigned the module on Supervised Learning, covering both regression and classification models. I was so thorough in my outline that we wound up splitting the content into two separate modules, and I built out both of them. Prior to this work, my knowledge of machine learning was minimal – when I took the Data Analytics boot camp, there had only been a single module on machine learning and it covered both supervised and unsupervised learning, as well as neural networks and deep learning. With that much covered in a single module, you can assume it wasn’t covered in very much depth. I had, honestly, found a lot of it confusing. But that meant when it came time for me to work on developing curriculum around supervised learning, I found a way to explain anything I didn’t initially understand well in a way that I thought would be easier for students encountering these concepts for the first time to understand.
When that course was complete, we moved into developing a full 24-week AI boot camp, for people who want to get into coding for AI with zero coding experience. I’m really proud of the work I did on that course so if you’ve ever thought about getting into AI but don’t know where to start, consider checking it out with one of the many universities that offer the course. I developed the modules on introductory Python, data collection (which primarily uses APIs but also goes into extracting data from tables on web pages, and the legal considerations), Supervised Learning (expanding on the content from the microbootcamp, I developed the classification module on my own and co-developed the regression module), and Neural Networks and Deep Learning part 1. It was in this final module I worked on that I am most impressed with my upskilling, as it afforded me the opportunity to introduce a day of content on recommendation systems by building and training a Restricted Boltzmann Machine, helping both myself and students better understand how tensors work in TensorFlow.
Prior to my developing this content, there hadn’t been a plan to include recommendation systems in the curriculum, and it was the one thing I felt had been missing. Because aren’t recommendation systems one of the things many non-technically minded folks are aware of that comes from machine learning, that would make them interested in working in that area? I know it was for me – my final project when I took the Data Analytics boot camp was a movie recommender. With the skills I have now, I know I could build something better, and it’s something I’m considering working on whilst I’m out of work so I have a new project to showcase my current skills.
We had really tight deadlines with the AI boot camp. The first cohort of students were already taking the course while we were still working on developing the content. I had to learn about neural networks, deep learning, and recommendation systems at the same time as I was developing the content on it, and yet I still managed to meet my deadlines ahead of schedule. On top of that, I went on a vacation to Malaysia, taking two weeks off work, in the midst of working on the supervised learning content. Still met my deadlines early. I enjoyed the challenge; I loved having the opportunity to learn on the job.
This year, my team shifted into developing an 8-week introductory Python course. It covered many of the same topics as the two weeks of Python in the AI boot camp, but in more detail and at a slower pace for those who may not be able to cope with the pace of a boot camp. I developed the modules on Data Structures (which I loved, because I’m a big fan of dictionaries) and Loops (which was interesting to introduce after functions, as it meant my approach to teaching it differed than it had in the past). Then I co-developed the module on object oriented programming (OOP), which gave me another opportunity to learn more, as I’d had limited experience with OOP in Python prior to this. I also got to develop unit tests for auto grading assignments and course work.
The final project I worked on and completed prior to the layoff was developing the introductory Python content for the Coding boot camp students, where it was being introduced to the very end of the course – after students already had weeks of experience with JavaScript and TypeScript. This was another fun project to work on because it meant I had to introduce Python at an even faster pace than in the AI boot camp, since I didn’t have to explain the basics of things like data types, conditionals, loops, and functions – I mainly just had to explain how to do them in Python. It gave me the opportunity to pick up my JavaScript skills again and use them to compare the differences in syntax, and demonstrate what you can do in Python that you can’t do in JavaScript.
So, when I was laid off, I still felt like I’d accomplished so much in three years. This blog covers the highlights, but I got to do other interesting things too. I had an opportunity to explore using IBM’s Watson, specifically with the text-to-speech API, and presented what I learned to the broader curriculum team. I was a panelist on an in-house neurodiversity panel twice. I also presented my language converter Flask app to the curriculum team, and a personal project to locate soup recipes based on different filters (I developed this as part of a writing competition so I might copy what I wrote about it at the time over to this blog soon) using JavaScript. I worked so hard on the AI boot camp content last year that I was promoted to Senior Curriculum Engineer in April. Everything that happened helped me feel more confident in my capabilities.
And I was already in the beginning stage of interviewing for a tech company I was really interested in working for just before I was laid off, thanks to a recruiter reaching out to me on LinkedIn. The skills I developed in MongoDB, AI, and machine learning in my previous role helped me through seven interview rounds in the subsequent weeks. I was so confident that this role was the universe gifting me the next steps I wanted to take in my life that I felt like I could focus on more than just the hunt for a new career. I still applied for other roles in order to meet requirements for unemployment benefits, but it wasn’t my primary focus.
I took the rest of my time off of working in order to focus on other things I knew I had to get through, that I felt like the universe was guiding me toward, so I could continue moving forward. After my last blog post had garnered so much attention, including from people who didn’t personally know me, I’d realised I had more story to tell and I was going to turn it into an actual memoir book. It was the best way for me to process the end of a relationship that had meant so much to me. I’d been working on writing it whenever I had free time during non-work hours, but being unemployed meant I now had a lot more flexibility to write whenever. So I wrote. And I kept writing. Until I ended up with a memoir over 200,000 words long. It’s not quite done – I still have some loose ends to tie up once I live through the experience, and then I’ll have to figure out how to edit the story. But 200K words in four months is an amazing accomplishment for me. If you’re interested in learning more and following along that journey, I’ve been posting reels to Instagram where I read short excerpts from my draft manuscript. I’m really looking forward to publishing that story though – it’s my most vulnerable piece of work yet.
One of the themes of my memoir is belief in one’s self, and how feeling undeserving of something we want leads to self-sabotaging behaviours. I have achieved great things through the power of self-confidence, and chased away other things I wanted when I didn’t believe it was possible for me to get what I really wanted. I needed to write my memoir in order to more fully comprehend those decisions and behaviours, so I could learn to believe I deserve the other things I want, too. This is why the improv tenet “mistakes are gifts” is so meaningful to me. It’s okay to make mistakes when we can learn and grow from them.
Here’s a clip of how I use that improv tenet in improv:
Now that my memoir has been passed off to a few friends to read and offer me feedback, and I just received a rejection from that tech company I had seven interviews for, I need to put more effort into looking for other job opportunities and showcasing my coding skills. Hopefully my next blog post will be about a coding project I decide to develop.
Whilst my writing will be taking more of a back seat while I look for work, I won’t be dropping my creativity entirely. I’m back in the swing of things with both stand-up comedy and, when opportunities arise, performing improv. During my time off, I reunited with my first improv group, YUM! (which is where the above clip is from), and it has been a blast already. We have another show coming up on December 7th at Leela in San Francisco at 7:30pm. If you want to come along, click here for tickets!
If anyone reading this knows about any open opportunities you think would be a good fit for me based on my experience, please pass them along to me on LinkedIn. I’m open to and interested in roles like Software Developer/Engineer, Machine Learning Engineer, Data Scientist, Data Analyst, Data Engineer, and I’d also consider more Technical Curriculum Development roles. The industries I’m most interested in working in are technology, education, travel, social media, or entertainment, but I’m open to other industries that could be a good fit as well.
I would prefer to work remotely because I’m a single mum, but I could work from an office in the San Francisco Bay Area (I live in Oakland), and would be open to relocation for the right opportunity, depending on the city/country (I’ve lived in Australia and Malaysia in the past, and there are a couple of other countries I could consider moving to besides those).
Autistic people like myself typically have a harder time than our neurotypical peers when it comes to the job hunt process because it’s not designed for us. That means I’m more likely to succeed in getting employment by non-traditional means or when someone recommends me first. Hence why I’m blogging to put myself out there.
