02 / Experience
Work Experience
My journey through AI engineering, ML research, and production deployment.
AI Engineer
e-Marketing.io
Sole AI Engineer responsible for designing and shipping the full suite of AI-powered products for a performance marketing agency and its clients — owning everything from problem scoping and model selection to deployment and iteration.
- ▸Built an AI Meeting Summarizer that converts hour-long recordings into structured briefs with decisions and action items — saving teams hours of follow-up every week.
- ▸Developed a Keyword Analysis Engine that replaced gut-feel content decisions with NLP-driven insights on trends, intent, and competitor gaps.
- ▸Shipped AI chatbots across social media and messaging platforms that qualify leads and respond instantly — keeping client pipelines active around the clock without human intervention.
- ▸Delivered a Lead Management Dashboard giving clients real-time visibility into pipeline status and full bot conversation history — everything in one place.
- ▸Built a WhatsApp Task Delegation system where teams assign, track, and close tasks via text or voice note — eliminating app-switching and keeping everyone accountable.
Data Science Specialist
LogiScope Technologies Pvt. Ltd.
Focused on making sense of massive, noisy log data — building ML and deep learning backends that turned raw system logs into actionable intelligence for monitoring and reliability teams.
- ▸Ran deep EDA on large-scale log datasets to surface hidden patterns that manual monitoring consistently missed.
- ▸Built and deployed anomaly detection models using ML and DL algorithms that flagged system irregularities in real time — strengthening monitoring before issues escalated.
- ▸Experimented across multiple analytical techniques to identify the most reliable signals within complex log behaviour, turning raw data into clear, actionable outcomes.
- ▸Collaborated with cross-functional teams to integrate findings into data processing pipelines and improve anomaly reporting frameworks end-to-end.
Data Science Intern
Celebal Technologies
Worked within a professional data science team during a summer internship — getting hands-on with the full pipeline from raw data to deployed models, and applying Azure Cloud to bring it all together in a real production context.
- ▸Cleaned and preprocessed large datasets end-to-end, ensuring model inputs were reliable before a single line of training code ran.
- ▸Implemented ML algorithms against real business problems — moving from experimentation to predictive models with measurable outcomes.
- ▸Leveraged Azure Cloud services to understand how production-grade data applications are architected and deployed at scale.
- ▸Collaborated closely with senior data scientists, absorbing best practices and contributing to cross-functional project delivery.