The AI Engineer: An Unexpected Journey*

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Hi.

My name is Azmi and I’m a Senior AI Engineer at AI Singapore. Every day I work on interesting projects together with highly motivated, capable and, most importantly, awesome colleagues to solve AI problems. How did I get to be this lucky?

To answer that, I would have to take you back 5 years to the end of 2015; to one of the lowest points in my professional career. At that time I didn’t feel lucky at all.

I found myself retrenched for the first time in my working life.

Act 1: An Unexpected Ending

Let’s start with a little backstory.

After graduating from university with a degree in Computational Physics, I found myself working in one of Singapore’s life sciences research institutes. I was part of a programme to develop national capabilities in Grid Computing (the precursor to Cloud Computing) after which I continued as a Software Engineer to support biomedical research for a total of three-and-a-half years. I then decided to make a change and found myself working for an international company that provided Geophysical services to Oil & Gas companies. As it turned out, I eventually spent more than 10 years with this company, starting off as a Geophysicist whose job was to process huge volumes of seismic data that represent the subsurface structure of the Earth. These data volumes would then be used by the Oil companies to identify potential reservoirs for exploration.

A seismic data processing geophysicist will generate 3D image volumes using large quantities of data and significant computing resources. This volume is then used by Oil companies to identify geological structures and potential hydrocarbon reserves.

(Image courtesy of USGS)

I really enjoyed my work. I became competent enough to progress through the ranks, advancing to become a Technical Trainer. I was eventually appointed as the Regional Training Supervisor for APAC, where I was responsible for the training management of about 800 employees across the region. Somewhere through all of this, I even completed a Masters degree in Geoscience to deepen my knowledge in my field.

It was around 2014 when oil prices started to slide downwards from the highs of more than USD100 per barrel. The prices came down to a point where it was no longer economical for Oil companies to invest in new fields. Any company that depended on the fortunes of the Oil industry was greatly affected by this, as many Singaporeans might probably remember from that time. Similarly, the company I was working for was adversely affected and continues to experience sustained difficulties. Even today, the Oil & Gas industry is still facing tough challenges compounded by COVID-19, which has seen effects ripple across the global economy. It was under this backdrop that the company had to retrench a number of its people at the end of 2015 in order to save costs. I’ve had family and friends who had gone through retrenchment but it feels different when it happens to you.

Act 2 : Out of the Fire and into a Maze

To be honest, I probably didn’t handle retrenchment too well in the beginning. There was a whole range of emotions that I felt at the time which would probably require an entire article to express. Fortunately, I won’t do that to you here.

After getting over the initial shock, I had to assess my situation. I had just come out of a 10-year job working for the same company. I didn’t know how to look for a new job. The last time I applied for a job, it was listed in the Ads section of the newspaper. I hadn’t even updated my resume in years. Fortunately, there was some support for this through various agencies like E2i, WSG etc.

Initially, I did what many people in my shoes would do; to find a job as close to what I had been doing in both job role as well as industry. I was fortunate enough to have received some retrenchment benefits so at the time I felt I could hold out, hoping that the Oil and Gas industry would recover. The industry is well-known for its cyclical nature and the hope was that the downturn would be just temporary. However it turned out that this was blind optimism. One month soon became two, which then became three months. Six months passed and I was not even close to finding a suitable job opportunity anywhere in Singapore or even in the region. It became clear that the downturn would be here to stay.

It was around this time that I began to look around to see what other job roles I could do. The online learning movement had started to gain more traction and it was then I came across this ‘thing’ called Data Science. Data Science caught my eye because being a Geophysicist was very similar in some aspects. Seismic Data Processing in Geophysics was about managing, processing and making sense of data. So with doe-eyed enthusiasm, my plan then became: “Let’s do some of these online courses and then I’ll be able to get a job as a Data Analyst. Easy Peasy!”

It turned out that I was wrong and not for the last time in this journey.

With time on my hands, I was able to complete a number of Data Science courses in quick succession over the next few months including some well known ones. Even with those ‘certifications’ in hand, I was still not getting any opportunities in the job search. In fact, I wasn’t even getting any interviews. I was getting extremely frustrated. My morale was at an all time low. I felt that I was missing some pieces in the job search puzzle but I didn’t know what they were.

So by this time, almost three quarters of 2016 had gone by with no silver lining in sight. This was not a fun year.

Act 3: The Fog Clears

I then heard from a friend about a Data Analytics training programme delivered by the Institute of Systems Science at NUS. They were running a training programme under WSG’s Professional Conversion Programme (PCP) which targeted PMETs who wanted to transition into Data Analytics. The scheme included job placements and real-world practical experience. I felt that practical experience was the key piece missing from my Data Science learning. On paper, it seemed that I was the perfect profile for this and I applied with renewed enthusiasm. Once again I was brought down to earth with a rejection. This was due to the limited job placements available (getting accepted and employed by a company prior to starting was a key requirement of the programme) and the large number of applicants. Out of desperation, I persisted with NUS-ISS and I was accepted to join the same training programme but directly as a paying student. The main difference between a PCP participant and myself was that I would not have a job at the end of the training.

The programme consisted of a month-long classroom-based training followed by a 6-month practicum at a company. It was during this period that I was more exposed to and began to be more interested in Machine Learning. For the project work, I was attached to HP where I built an anomaly detection model for one of their manufacturing processes.

I believe it was this practical work experience that became the key for me to land a job in this new field as it was a demonstrable outcome of all my learnings in Data Science. After completing the programme, I was able to get a new job as a Data Engineer at a local Data & AI Consultancy company. This company was key in my initial development in the Data Science field. They encouraged me to work towards and attain technical certifications (Microsoft Certified Solutions Expert). Secondly, they allowed me to utilize my previous skillsets to gain a lot of exposure and experience in the industry by delivering public presentations, training courses and participate in trade shows. They also encouraged my interest in Machine Learning by putting me in the Data Science team and working on ML focused projects.

In mid-2019, I saw a role advertised at AI Singapore. I applied to join as an AI Engineer and I’ve been here ever since. I was struck by AI Singapore’s ‘Grow our own timbre’ philosophy. In the AIAP programme, I see apprentices who are going through similar journeys that I had to go through a few years earlier. As an Engineer and a Mentor, I believe it’s my duty to help train these apprentices to transition into Data Science and be successful AI Engineers when they complete the programme.

Throughout this new career path that I’m forging, I’ve also tried to find opportunities to incorporate skills and knowledge that I’ve accumulated over the years. For example, I was able to learn new programming languages, R and Python, relatively easily and am able to build robust, complicated ML systems based on experiences developed as a Software Engineer early in my career. I’ve used my technical training experience not only to mentor Apprentices but also to develop new technical content for AISG and to make external presentations when called upon. I use my experiences as a Geophysicist to handle technically challenging AI problems, manage large quantities of data and to engage the customers so that we can solve the project together. I was even able to use some knowledge from my Geophysics background in one of the projects which required some knowledge of signal processing and acoustic waves.

As an AI Engineer, I also deliver at public events such as AI for Everyone (pre-COVID).

Reflections

The past five years have been professionally challenging, triggered by an event that I hope people will never experience in their careers. However in some perverse way, I’m glad that it happened. I might not have been on this path and would not be writing this article otherwise. I also feel that I’ve grown mentally stronger because of it and will be more resilient to future hardships. Could I have done better? Sure, as they always say ‘hindsight is 20/20’. If I had a time machine, I would probably tell my younger self the following:

  • “Don’t stay in the bubble”: When I was working in the Oil and Gas industry, I wasn’t really paying any serious attention outside of Geophysics and industry. Had I widened my attention span, I would have known about the upcoming trend in Data Science and Machine Learning. This could have accelerated my entry into this new domain.
  • There is a common axiom that you should never stop learning. Never more true. With all the free and affordable online resources available, there is no reason to not do so. The act of learning itself is also important. Studies have shown that continual learning can help arrest cognitive decline as one grows older.
  • The growth of online learning has been a boon to many people. It has made learning new knowledge much more accessible. However, you need to realize that completing the online learning is only half the battle, you will also need to develop the real-world practical skills that will allow you to apply this knowledge.
  • Finding a job is a skillset on its own. Learn to utilize career coaching services and recruitment agencies more effectively. Write better resumes. And pay more attention to building a better online professional profile e.g. LinkedIn.
  • Do an honest audit of your own competencies and identify those that can be transferred into the new domain.
  • Above all, do not forget your mental health. It is important to stay motivated and not lose hope. Don’t be embarrassed to seek help.

For my final thoughts, as I’m writing this article in 2020, COVID-19 has profoundly changed the world that we know. Many people are facing personal and professional challenges as a result of this pandemic either directly or indirectly. I can’t really speak about the personal challenges but maybe I can provide some solace for someone who is going through professional challenges now. I hope you will read this and find some inspiration or motivation to keep fighting on. The future is uncertain but if you endeavor, there’s always a chance that you’ll come out the other side better and stronger.

* Literary fans may recognize Tolkien’s The Hobbit references in the title and section headers. You were not imagining it!

Author

  • Azmi is Senior AI Engineer for AI Innovation at AI Singapore, a national programme launched by the National Research Foundation (NRF) to anchor deep national capabilities in AI, thereby creating social and economic impacts, grow the local talent, build an AI ecosystem, and put Singapore on the world map. Azmi has a Diploma in Data Analytics from NUS-ISS, M.Sc.in Petroleum Geoscience from Royal Holloway and B.Sc. in Computational Physics from NUS.

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