Jan 2025 – Present · 1 yr 4 mos

• One of the technical advisory board members for https://sampleapp.ai/

Aug 2024 – Aug 2025 · 1 yr · San Francisco Bay Area · Hybrid

• Focused on developer advocacy for AI agents and LLM workflows with the aiXplain SDK.
• Served as a main contributor to marketing campaigns and product strategy, aligning developer feedback with business goals.
• Designed and launched a certification course to onboard and upskill developers.
• Created Agent O’Clock webinar series to showcase practical AI agent use cases.
• Built technical demos, tutorials, and prototypes highlighting agent workflows.
• Organized and spoke at events, workshops, and hackathons to grow developer adoption.

Aug 2023 – Mar 2024 · 7 mos · Remote

• Volunteering as a technical content writer to write technical blogs and other content in AI space

Oct 2022 – Present · 3 yrs 7 mos · San Francisco Bay Area

• Hosting and managing AICamp meetups for ML/AI in the SF/Bay area
• Networking with the AI community
• Inviting speakers and sponsors for the tech events

May 2021 – Aug 2022 · 1 yr 3 mos

• Built a prototype model for automatically generating search queries that effectively match those from Google ads using a large language model.
• Led the task of improving ad copy matching task for digital marketing optimization using NLP techniques like Named Entity Recognition and language models
• Helped the team to set up experiments to run new ad campaigns from the Google Ads console using A/B testing and statistical methods.
• Researched into building FAQ generation tool for marketing optimization using state-of-the-art NLP models like transformers and other attention models.
• Tools and Technologies:
• Python (HuggingFace, PyTorch), AWS SageMaker

Nov 2016 – Aug 2020 · 3 yrs 9 mos · Spring lake heights, New Jersey

• Duties at Ozmosi (but not limited):
• Led the R&D work for the team to identify most relevant techniques to automate day-to-day analysis of clinical trials data and other sources of pharma data
• Performed unstructured text-heavy data wrangling and cleaning along with relevant information retrieval using natural language processing (NLP) techniques in Python
• Built supervised and unsupervised machine learning models and used NLP techniques like n-grams to detect patterns, trends from various data sources like clinical trials data, publications and scientific journals
• Used statistical analysis of clinical trials data for basic data analysis reports
• Explored, examined and interpreted large volumes of data in various forms to support clinical and pre-clinical searches for client deliverable and product development
• Built end-to-end process of cleaning raw JSON data, and published it into the database, using Ruby
• Managed and monitored databases using AWS services
• Tools and Technologies:
• Database management: SQL, MongoDB, Postgres, AWS Redshift, AWS EC2
• Languages: Python (scikit-learn, numpy, pandas, gensim, NLTK and more), Ruby, Shell

Sep 2015 – Dec 2015 · 3 mos · Lancaster, Pennsylvania Area

• I helped the data science team to get a detailed insight into patients' comments from the medical survey by using sentiment analysis to classify/predict the satisfaction level of patients based on their comments. Overall the goal was to perform data analyses on medical surveys to provide detailed feedback to the medical providers.
• Languages/Packages/Software used: Python, R, SQL, NLTK, Pandas, scikit-learn, Power BI, R Studio and SQL Server Management Studio 2014.

Jul 2015 – Aug 2015 · 1 mo · Lancaster, Pennsylvania Area

• I performed sentiment analysis on the text comments written by patients in the survey for their doctors. With that I also used data mining techniques in order to optimize the process and increase the number of patients to fill out the survey.
• Languages/Packages/Software used: Python, R, SQL, NLTK, scikit-learn, R Studio and SQL Server Management Studio 2014.