Meet Ilanchezhian, Senior Machine Learning Engineer
by Ilanchezhian
I am Ilanchezhian, and I work as a Senior Machine Learning Engineer, in Bangalore, India. I have predominantly worked on developing Natural Language Processing (NLP) applications and deploying machine learning applications into production with Azure. I like to read online blogs and take courses on recent technologies to keep me updated. My hobbies are taking photographs, playing video games, and cycling.
What did you want to be when you grew up?
I was always fascinated by computers and interested in them. I remember reading about the different computer generations at school and had an impression that the fifth generation of computers with AI capabilities would be huge and never-ending.
When I started learning about BASIC Programming Language at school, it was a nightmare as I never really understood it. Later, when I switched to C/C++, Computer Science became my favourite subject at school, so much so, that I chose it as my undergrad major.
Can you tell us a bit about your background?
I had dabbled a bit with Java during my initial years and started learning python programming language shortly after completing my undergrad. I reached out to quite a few people working on AI projects and gathered information on the tools and technologies used and started learning python, NLP techniques such as document classification and named entity recognition, machine learning libraries, and deployment techniques. I also took advantage of self-paced MOOCs to improve my domain knowledge.
I decided to transition to industry post the completion of my Master's degree. As part of my thesis, I conducted research in the field of Text Mining and completed a project on Document Classification with Ontologies. My passion for research continued throughout my postgraduate years wherein I worked on NLP and simultaneously developed an interest in open-source technologies.
I completed a project on Named Entity Recognition from images, which used Tesseract OCR and converted it into a web application with flask and deployed it on minikube, which helped me immensely in solidifying my grasp on the MLOps lifecycle.
Why did you choose this career path?
Artificial Intelligence was one of the growing sectors that appealed to me as it matched my technical skills. In an ML lifecycle, from model development to deployment, I got to spend more time with deployment and maintenance in production. I also found deploying a model at scale in production a very challenging and interesting area. When looking for opportunities at Haleon, I started looking for Machine Learning Engineer roles in order that I could spend more time with deployments.
What do you do day to day?
As a Senior Machine Learning Engineer, my priorities are working on the projects assigned to me, and internal tasks like building a common model monitoring dashboard to visualise the model performance.
I start my day by checking on any approaching deadlines and updating the tasks in Jira. I also have a 1:1 weekly call with my Line Manager to discuss priorities and divide them into daily and weekly tasks. Usually, we work on a 2-week sprint for a project. During planning we will create a task that can be completed in a sprint and the sprint will be closed with a demo and retrospective. During the sprint, I will spend time reviewing PR, helping team members, and documenting.
I also dedicate time to learning and keep an eye on recent developments in Machine Learning.
Are there any areas of DS/ML that you feel will be particularly prominent in the future?
In Healthcare DS/ML is expected to play an increasingly important role in improving patient outcomes and reducing costs in healthcare through the development of personalised medicine, predictive diagnostics, and drug discovery.
Customer Service: AI-powered chatbots and virtual assistants are becoming more useful and will continue to be widely used for customer service in various industries. For instance, within the appropriate responsible AI framework, ChatGPT can be custom trained to chat about a company’s products and services, to give better utility.
Manufacturing and Supply Chain Management: DS/ML has the potential to revolutionise the manufacturing industry, for example using predictive demand-supply, quality control, augmenting workforce, and optimisation of production processes.
How do you keep up with the field?
I read research papers, attend conferences, and workshops and follow the work of leading researchers in the field to stay informed of new developments and trends. As a team, we connect every week with the Microsoft team to discuss recent trends.
Every week a state-of-the-art model is getting released that surpasses previous benchmark scores, however, it is difficult to keep track of all of them. As an alternative, when I am tasked with new technology, I try to find the related community on LinkedIn and Twitter, to follow up on their latest research and implement them.
What do you like most about working at Haleon?
Haleon provides me the opportunity to develop and apply cutting-edge AI and ML technologies to solve real-world problems, collaborate with talented interdisciplinary teams, and potentially have a significant impact on society. As an ML Engineer, I have collaborated with different projects which covered NLP, computer vision, and time series forecasting, which makes my job more engaging and interesting. We have excellent learning resources like LinkedIn Learning, and Pluralsight and are well supported by our Line Manager through regular meetings with Microsoft for upskilling. With Haleon, I feel very young and growing every day.
