January 01, 2021

My Experience as an Associate Machine Learning Developer with the AltaML Applied AI Lab

My Internship Experience as an Associate Machine Learning Developer with the AltaML Applied AI Lab

The AltaML Applied AI Lab launched in October 2020 with the goal to create a talent pool of machine learning innovators by bridging the gap between academia and industry. In this blog post, we the interns, of the first Cohort of the AltaML Applied AI Lab share our experience to give a peak behind the curtain on our journeys. For those of you interested in applying, or learning more we hope you find our 6 different perspectives useful insightful!

How did you find out about the Applied AI Lab? Why Did you Apply?

[Keith] The posting was sent to me by three people in my network. I applied because I had recently graduated from the data science program at the University of Calgary. As part of the program, AltaML presented to students about the company and its vision. Having my interest sparked by their presentation and the support from my network, I was keen to apply.

[Sam] Despite the fact that I had been on the lookout for openings at AltaML, stumbling on the advert was quite random as I was scrolling on Twitter and I saw the advert and everything that was being advertised just seemed a little too tailored to what I was looking for so I immediately got to applying because I knew there were going to be a lot of applicants, who just like me wanted to crossover from academia to the industry side. I started brainstorming ways to standout in my application and since I already knew about AltaML and their visions aligned with mine it was easy to honestly fill out the questions that were asked about motivations for applying and expectations. 

[Yingyu] I found the Applied AI Lab online because I was looking for an opportunity in the ML/AI field. I researched AltaML and the internship program, then decided to apply for it. AltaML has an impressive impact on ML commercialization and works for partners in various industries. I’d like to work in an environment where people work hard and be supportive of each other to achieve shared goals, which fits AltaML’s company culture. The internship program also provides opportunities to let interns get hands-on experience by working with real-world ML projects, which I think will be helpful in my career development.

[Isaac]  After COVID hit, I made the decision to focus on pivoting my career to data science & ML (a field I love!).  I decided to follow AltaML on LinkedIn after seeing some of the amazing things that they do.  When I saw the post for the Applied AI Lab, I thought to myself “wow, I’d love to do that... but I’m definitely not going to make the cut”.  That being said, I applied anyways because it’s always been a dream of mine to get the “welcome to the nerd zone!” gif!  In the end, I guess I did make the cut!  

There are two sections to the interview process, with the first being a technical coding test, and then an interview.  Be sure to brush up on your Python & ML skills!  I’m fairly confident in my coding skills, but having to solve ML problems on the spot was definitely a challenge!

What was your first impression of the Applied AI Lab? What is the structure and expectations of the program? Would you recommend this initiative to prospective ML professionals? If so, why?

[Jamie] There was a lot more excitement around the internship than I realized. I knew this was the first cohort so there would be a certain amount of novelty, however I didn’t realize how much interest there would be from all areas of the company, as well as externally. It was very cool to see the enthusiasm from the mentors and managers, they clearly really want this project, and of course, the interns, to succeed, which gave me a very positive feeling immediately. 

The structure is rather informal. We are working on projects in pairs, along with a mentor. We are encouraged to explore all of our ideas and given feedback on them, rather than being expressly told how to approach a problem. The expectations so far have been very straightforward – we are here to learn as much as we can, and the more we put into the experience, the more we will get out of it.

I would absolutely recommend applying for this internship, and in fact I already have made that recommendation to several people. The amount of exposure we are getting just from being in this program is much greater than we would be able to get doing anything else.

[Keith] I highly recommend this internship. Every day is a new opportunity to learn and apply new skills.The partner companies are there along with your mentors and manager to create an experience that not only provides value to all involved but also gives room to learn and develop technically and professionally.

[Sam] My first impression on the day we started the internship was that this was going to be a very hands on experience and that what they had planned for us was above my expectations. Further into the internship, my impressions were spot on and because they had thoroughly evaluated our skills and personality they were able to partner us with the right industry partner which ensured that we could output with maximum performance. This helped me improve my skills as a machine learning engineer as well as a developer and  enhanced my sense of responsibility as a contributor to an impactful project.

Structurally,  we were given autonomy to work on the use cases but we were also paired with mentors who were there to help us out if we had any blocks which were inevitable due to  lack of experience / expertise, and this is one of the parts of the internship I appreciated the most because you could ask the mentors at any point for help either technical help, brainstorming  ideas or just clarification on ML know-hows and the mentors were very helpful and generous with their time and knowledge. These are resources that are not always available to you and I was grateful to have that. 

Yes, I would recommend this initiative anytime, anyday, anywhere. My advice to prospective applicants is that the Applied AI initiative is the best pathway to cross over to the industry side, there is a ton of hands-on experience and you get to contribute to a project that has real-life implications. 

[Yingyu]  The Applied AI Lab provides a great platform for me to understand all the processes of an ML project. There are training and presentation sessions in each stage, which allow us to learn how to work on the ML project. We can learn from experts who have many years of experience in machine learning, computer vision, NLP, and project management. We also can learn new tools and always get support from the mentors. I would highly recommend the program. The interns are not only developing their technical skills but also getting guides on what to improve would let us be professionals in the field.

What did you learn while working with your industry partner?

[Keith] Presenting weekly and being asked in depth questions regarding methodology was one of the most beneficial aspects of the internship. Data science involves many technical components but storytelling cannot be overlooked as it is how you convey your findings that impacts understanding and ultimately convinces your audience. In addition to that, the guidance from mentors to learn new techniques and push past your knowledge base into new areas was incredibly helpful as well.

[Sam]  Personally I think, business communication was one of the areas that I gained confidence in  the most due to this internship. Communicating your analysis, and rationale to the partner was a constant process in this internship and so this presented the opportunity to actively work on and  improve this skill. 

On the technical side, in order to solve my use-case I had to learn some new techniques and tools. The AltaML Applied AI initiative also provided us with access to Udemy and so if I needed to learn a skill for my project I had all these resources at my disposal and therefore I was always able to drive my project forward and  grow as a machine learning engineer.  

[Yingyu]  Working with an industry partner allowed me to consider the impact of  ML/AI on its business. My business acumen has developed, which allows me to have a deeper understanding of the industry,  their business problems, and how I can help them. Business communication is also what I have learned in three months. The skill of presenting technical information and results to non-technical audiences is very important for your partner to understand what you can help with their business.

What was your background coming into the program and how did you leverage that to your advantage?

[Isaac] I have a bachelor's degree & college diploma in mechanical engineering.  During my education, we hardly touched on programming, or anything to do with data science.  Once I got out into industry (directional drilling/upstream O&G), I started to work with data on a daily basis, and quickly realized that I was doing a lot of things that data scientists do on a daily basis.

As I continued to improve my skills with software development, I quickly realized that I loved building software and digging into data more than typical mechanical engineering.  During COVID I had the chance to work with a start-up on their backend API, and spent some time improving my understanding of ML and Python in general.  I think my background of developing production level code and working with data really helped me excel at the internship.  The bulk of the “work” in an ML project is building a data pipeline, and getting your data into a format that’s clean and ready for training a model. Being able to quickly complete that part of the ML development process allowed me to focus on  modeling and how to analyze the quality of the models I produce.

[Jamie] I have a bachelor’s degree with a double major in pure and applied mathematics, and a concentration in cryptography. It involved next to no programming, however I always wanted to teach myself. After graduating, I worked for a few years at a car dealership, during which I automated many processes and focused on improving efficiency. Teaching myself programming in my spare time made this immeasurably easier. In my application, I was able to leverage my experience in automation, as well as my background in mathematics, which gives me a good understanding of the theory behind most machine learning algorithms. Coupled with completing several online courses in machine learning and data science, I think this was crucial to my success.

[David] I have a bachelors in Mathematics with a concentration in statistics. Before COVID hit, I had no experience in machine learning and AI besides a few regression courses. My background in stats 100% accelerated my learning in ML/AI, and in the span of a few months, I completed two online certificates while working on my personal project. Being forced to analyze results, write papers, and present to my peers in university gave me the skill to translate the nitty-gritty that data science can often be, to something ‘that can be shared with my grandma’. So while I can’t point to one thing that I leveraged, the takeaway is to be yourself and use the things that make you unique. 

[Keith] I come from an economics background. I decided to pursue the data science diploma from the University of Calgary and applied to the AltaML internship program after I had completed it. I leveraged this experience by highlighting the dual nature of my interests in finance and machine learning and speaking to my previous co-op experience in data analysis. I think this helped my application progress.

[Sam] My educational background is in Biomedicine and Computer Science, professionally, my background is in Data Analytics for a Digital Marketing firm. I think having applied some ML techniques for work and being able to talk about that, helped my application. 

[Yingyu] My background is in mechanical engineering and industrial engineering. Solving operational and optimization problems in industries requires knowledge of statistical analysis and mathematics as well as technical skills such as programming, data mining, and visualization. I worked really hard to handle these skills in order to be prepared for starting my career in the data science field. Machine learning and AI has widely used in these industries, having an engineering background is also helping me to quickly understand data and gain insights.

What should I focus on to prepare for the internship? And what resources do you recommend when preparing to apply / interview?

[Jamie] For the initial application, make sure you review basic statistical and machine learning concepts, and try to dive into some more advanced topics as well. The technical test started out fairly easy but became difficult quite quickly. For the coding part, doing practice competitions on Kaggle will be really useful. 

Once you get through to the interview, review your machine learning algorithms, and make sure you know how you will be able to apply the knowledge you have gained in previous experiences to the applied AI lab. Also, take time to look into AltaML and the partner companies if you have not done so already. Knowing a little about the companies could definitely set you apart from the crowd. 

One thing I would certainly do differently if I was starting over, would be to connect with the other interns as early as possible. This internship is absolutely flying by, and I wish I had more time to learn from them!

[David] Coming from a pure statistics background, I definitely would have prepared my programming a lot more - although, I cannot overstate the value of understanding machine learning algorithms and knowing mid-level statistics. 

[Sam] Revising my ML knowledge, all the basics, interview questions and tips were the most relevant areas to focus.  I used the Analytics Vidhya Comprehensive ML interview guide, and did some coding practice questions on Hackerrank

About the Applied AI Lab

The Applied AI Lab was created to accelerate applied AI development. The AI Lab is a collaborative industry-led initiative, partnering with ATB, Suncor Energy, Spartan Control, and TransAlta. It helps bridge the talent gap between academic and applied skills by providing interns with guidance and access to real business problems, data, and industry partners. Over the 3-year program term approximately 240 individuals will have the opportunity to gain hands-on experience in applying AI.

The AI Lab has a new Cohort launching every January, April, July, and October. Our 2021 April internship is now open. Follow our official Twitter channel to get news, or visit our website

For more information contact:

Danielle Gifford, Senior Manager AltaML Applied AI Lab 

Email: [email protected] 


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