AI Enthusiast. Engineer. MBA Finance
π¬Data is how we listen to reality, but data science is how we translate what we hear into something we can understandπ‘
π Get in touch with me π π
πGitHub | βοΈakash.mathur2289@gmail.com |
βοΈMedium | π’LinkedIn |
#οΈβ£Kaggle | π€Space |
ππ¨π½βπ»Generative AI Applications β Project Portfolio π
Senior ML Engineer (Sep 2024 β Present)
60%
faster proposal responses by engineering a RAG
system with agentic
memory, tools, and custom prompts, accelerating RFI
evaluations and enabling quicker sales decisions.hybrid
search engine with LLM
-powered re-ranking, reducing time to insights
by 50%
and making global data platform more intuitive and user-centric.LLMs
to generate task-specific synthetic
data using PyTorch, enhancing model performance and reducing bias
in AI systems.medallion
architecture to build scalable pipelines that cleaned, enriched, and secured unstructured
data, making them auditable
and AI
-ready.Senior ML Engineer β Automotive Supply Chain Technology & Aftermarket (Jun 2021 β Aug 2024)
$500k+
in revenue by architecting end-to-end product on AWS
that forecast Vehicles Scrappage
. Setup Feature store and model monitoring
with SageMaker
to track and analyze metrics.deployment
and serving
with FastAPI through an efficient CI/CD
integrated serverless workflow using AWS, Docker, Terraform and GitHub.80%
by architecting end-to-end application on AWS. It recommends top news articles through similarity
search and summaries generated from a fine-tuned
FLAN-T5 model.sentiment
analysis using a fine-tuned
RoBERTa model and identifying prevalent issues using topic modelling
via BERTopic on AWS.Assistant Manager - Quantitative Modelling (Nov 2018 β Jun 2021)
90%
by designing ETL
pipelines tailored for large-scale data and leveraging ARIMA
for revenue forecasting using Databricks
.Analyst, Advanced Analytics - Global Markets Technology (May 2015 β Nov 2018)
ETL
pipelines, enabling precise identification of high-risk hedge fund investors with the Random Forest classifier.Dimensionality Reduction
and Clustering
Techniques to identify distinct client groups, leading to deeper customer understanding.π Technologies | π Interests |
---|---|
β’ Languages: Python, SQL, Spark β’ Machine Learning: Scikit-Learn, PyTorch, LangChain, LlamaIndex, Faiss, NumPy, Pandas, MLflow, TensorFlow, NLTK, spaCy, OpenCV β’ Cloud: AWS (SageMaker, Lambda, Batch, Step Functions, ECS, ECR, API Gateway, S3), Azure (Machine Learning, Data Factory, Databricks, DevOps), β’ MLOps: BentoML, MLflow, DVC, Docker, Terraform, CI/CD, Git, GitHub Actions β’ Visualization: Tableau, Power BI β’ Database: MySQL, SQLite, Vector Databases |
β’ Generative AI β’ NLP β’ Recommendation Systems β’ MLOps β’ Stock Market Analysis, Macroeconomics β’ Swimming, Yoga, Meditation, Cooking |
Post Graduate Diploma in Management - Financial Services | K J Somaiya Institute of Management, Mumbai, India | 2013-2015 |
Bachelor of Technology - Electronics & Communication | Rajasthan Technical University, India | 2008-2012 |