Machine Learning Engineer

LAKSHMI SRUTHI

************@*****.*** • +1-801-***-****)

PROFESSIONAL SUMMARY

Versatile and driven Machine Learning Engineer with over 5 years of experience delivering production-grade ML models for high-stakes domains, including fraud detection, risk scoring, and classification of unstructured data. Adept at framing ML problems end-to-end—from data sourcing and feature engineering to scalable deployment on AWS. Passionate about turning complex, messy data (web, geolocation, imaging, etc.) into actionable insights through NLP, deep learning, and classical machine learning approaches. Known for a bias toward execution, cross-functional agility, and full model ownership in fast-paced, agile environments.

EMPLOYMENT HISTORY

AI ENGINEERING ANALYST ACCENTURE, INDIA, FULL TIME May 2021 – April 2023

•Led design and deployment of real-time fraud detection models using NLP and tabular classification techniques—reduced false positives by 22% and saved clients $1M+ annually.

•Built an automated pipeline to classify unstructured healthcare claim text using BERT/RoBERTa, deployed with MLflow and Docker

•Developed production-grade Spark + AWS Glue pipelines to process millions of claim records daily.

•Owned end-to-end delivery: framing problem feature extraction model training/tuning API deployment monitoring.

•Collaborated closely with product and backend teams during agile sprints to release biweekly production updates.

DATA ANALYST UNITED SERVICES, INDIA, FULL TIME Nov 2018 - April 2021

•Developed Python/SQL pipelines to ingest and clean web-scraped business data for segmentation and scoring.

•Applied clustering and PCA to analyze behavior profiles of customer segments across multiple geographic regions.

•Partnered with software engineering and QA teams to implement models as RESTful APIs and dashboards.

•Engineered monitoring and alerting scripts for production data integrity across Redshift, Athena, and PostgreSQL.

ASSISTANT RESEARCH ANALYST SAINT LOUIS UNIVERSITY, MO, ON CAMPUS JOB Nov 2023 – April 2024

•Built computer vision and classification models to identify recyclable waste in real-time video streams.

•Integrated labeled datasets and trained models using TensorFlow + Label Studio, deployed on Seldon + Kubeflow for scalable inference.

•Conducted empirical research to benchmark performance across model variants.

•Participated in sprint planning and model evaluation reviews across data science and engineering pods.

EDUCATION

M.S. INFORMATION SYSTEM SAINT LOUIS UNIVERSITY Aug 2023 – May 2025

Saint Louis, MO, USA

POSTGRADUATE IN DATA SCIENCE GREAT LAKES INSTITUTE OF TECHNOLOGY March 2020 – April 2021 AND ENGINEERING

Chennai, India

SKILLS

ML/AI: NLP, LLMs (BERT, RoBERTa), Text Classification, Transformers, XGBoost, Random Forest, CNNs, Time Series, PCA, Clustering

Programming: Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow), SQL, Spark

ML Engineering: MLflow, Docker, CI/CD, Apache Airflow, Seldon, Kubeflow

Data Engineering: AWS (S3, Glue, Lambda, Redshift, Athena), Snowflake, PostgreSQL, Apache Spark, OpenSearch

Dev Practices: Agile, Git, JIRA, GitHub Actions

Visualization: Power BI, Tableau, Matplotlib, Seaborn

Collaboration: Agile, Cross-functional stakeholder engagement, Technical Documentation

PROJECTS

GenAI-Powered Customer Feedback Classifier

Python, Hugging Face, LangChain, Power BI

Collected open-ended product reviews and built transformer-based classifiers (BERT) to bucket feedback by themes (delivery, UX, pricing).

Summarized insights using LLM-based text summarization and visualized feedback heatmaps in Power BI.

Satellite Image-based Crop Health Prediction

PyTorch, OpenCV, GeoTIFF, AWS S3

Processed NDVI satellite images to classify farm zones into healthy/at-risk categories.

Built a pipeline with PyTorch CNNs, image augmentation, and region-based aggregation.

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