Akshat Malik — Software Engineer
As a software engineer, I bring nearly five years of hands-on experience in building and scaling robust systems. Complementing my technical expertise, my academic pursuits have led to authoring two papers for submission to the EMSE journal, showcasing my deep understanding of the field. During my tenure at Atlassian, I was responsible for constructing a reporting platform using Java (Spring Boot) and AWS services. This platform efficiently processed tens of millions of events daily, enabling over 200,000 users to access their data. Additionally, I contributed to a periodic report delivery system, achieving a remarkable 99.999% success rate in delivering analytics reports to users. A significant achievement was optimizing the dashboard's performance, where I managed to reduce loading times dramatically from 18 seconds to just 0.4 seconds. At Soroco, my focus was on developing a robust data analysis platform that significantly enhanced the productivity of the analytics team by 40 times. This platform was built using Python, Flask, Redis, and RabbitMQ, ensuring scalability and efficient distribution. Furthermore, I designed a user management portal using Go, streamlining the onboarding process and enabling efficient management and monitoring of user activities. As a research student at the SAIL lab, under the guidance of Dr. Bram Adams and Dr. Ahmed E. Hassan, I concentrated on enhancing the privacy of machine learning models. My approach involved a novel method of representing tabular data as graph data, followed by the application of graph anonymization techniques. This technique not only matched but in some cases surpassed the performance of state-of-the-art methods, achieving similar privacy scores. My research led to the authoring of two papers for the EMSE journal, one currently under revision and the other under review. Lastly, in my role at the National Bank of Canada, I specialized in fine-tuning Large Language Models (LLMs) to assess chatbot performance for accuracy and validity. I also innovatively employed LLMs to automate the manual annotation process, enhancing efficiency in data handling.
Stackforce AI infers this person is a SaaS-focused Software Engineer with expertise in data engineering and machine learning.
Location: Kingston, Ontario, Canada
Experience: 4 yrs 6 mos
Skills
- Mlops
- Artificial Intelligence (ai)
- Data Privacy
- Machine Learning
- Software Engineering Practices
- Cloud Computing
- Data Engineering
- Software Development
- Database Management
Career Highlights
- Reduced dashboard load times from 18s to 0.4s.
- Increased analytics team productivity by 40 times.
- Authored two papers on privacy in machine learning.
Work Experience
Microsoft
Software Engineer (2 yrs 1 mo)
National Bank of Canada
MLOps Intern (7 mos)
SAIL Lab
Research Assistant (1 yr 7 mos)
Atlassian
Software Engineer II (1 yr 2 mos)
Software Engineer (1 yr)
Soroco
Software Engineer (2 yrs 4 mos)
Education
Master's degree at Queen's University
Bachelor's of Engineering at RV College Of Engineering
