Hi, I am
Software Engineer, AI & ML
Throughout my 9 years as a Software Engineer, I've cultivated 5 years of hands-on expertise in Data Science and Machine Learning, creating a powerful synergy of software development proficiency and data-driven strategies. My background includes robust backend development skills with Python, Node.js, FastAPI, MySQL, and DynamoDB, complemented by strong frontend capabilities in React. I have experience in designing and deploying scalable serverless applications on AWS, utilizing AWS Lambda and AWS Cloud Development Kit.
In my recent work, I developed a generative AI application that streamlined the recruitment process by evaluating and ranking candidate CVs based on their alignment with specific job descriptions and built a Generative AI interview conducting bot using LLM for rating candidate answers that lessened the workload of the recruiting team. Previously, I led my team to transition to data-driven decision-making through ML implementation, building a sales forecasting model that increased profit by 15% and a recommender system that increased sales across product categories.
I am passionate about applying my combined expertise in ML and Data Science to drive impactful, scalable solutions and bridge the gap between software engineering and AI-driven innovation. If you're seeking a versatile engineer with a strong product mindset, a passion for machine learning, let's connect!
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This app uses Gen AI to evaluate and rank candidates based on how well their CVs match a given job description, helping recruiters streamline the candidate selection process.
This application predicts the driver churn rate for a ride-sharing company using machine learning algorithms.
This system scans daily market data to generate trade signals, automatically places orders, and saves trade data to a database.
Was a member of the core team that developed Grassdoor, an e-commerce website and its associated admin portal using ReactJS.
Led the company's transition to data-driven decision-making through ML implementation.
Communicated with stakeholders to gather requirements and provided recommendations that considered both business and technical viability, resulting in reduced development time.
Built an ML model using the Random Forest algorithm to predict monthly sales resulting in a 15% increase in profit and better inventory planning.
Built a recommender system using the Apriori algorithm resulting in increased sales across product categories.
Developed sales analytics dashboards by constructing efficient SQL queries to aggregate data from various sources
Increased the engineering team's efficiency by recruiting, training, and supervising a group of 7 junior developers.
Developed cost-effective serverless microservices using AWS CDK, AWS Lambda, DynamoDB, and API Gateway.