Shreya Singh Joshi
I am a Machine Learning and Data Engineering professional with 10+ years of experience designing and automating data pipelines across AWS, GCP, and Azure.
About
I am a Machine Learning and Data Engineering professional with 10+ years of experience designing and automating data pipelines across AWS, GCP, and Azure. I specialize in building end-to-end ML solutions, NLP, and computer vision, and I am passionate about optimizing data architectures, reducing pipeline latency, and deploying scalable ML models into production. I thrive in cross-functional teams, translating complex data into tangible business impact.
I enjoy mentoring teams, driving best practices in data governance and ML Ops, and continuously learning new tools to solve real-world problems in fast-paced environments.
- Joined November 2025
Industry experience
- Software & Internet
- Professional Services
Work experience· 8 roles
Designed and deployed a Node.js web platform to visualize dynamic pricing insights, statistical trends, and vendor comparisons to enable real-time decision-making. Architected and automated ML pipelines on AWS (Lambda, S3, EC2, DynamoDB) for computer vision use cases, covering data preparation, model training, fine-tuning, evaluation, and deployment. Built automated model monitoring and retraining workflows using AWS Lambda, Python, and shell scripts to sustain model accuracy and reduce manual maintenance. Optimized DynamoDB schemas and S3 storage for semi-structured data and model metadata, improving query performance, scalability, and retrieval speed. Implemented real-time and batch inference pipelines with asynchronous APIs and scheduled jobs, delivering low-latency predictions and high-throughput processing. Enhanced pipeline performance through efficient job scheduling and configuration tuning, cutting deployment latency and compute costs. Owned the end-to-end delivery lifecycle f
Contributed as a part-time data science intern, supporting ML initiatives and platform development.
Implemented and tested Airflow DAGs for automated data ingestion and processing. Created and deployed Snowflake tables and infrastructure using Terraform for consistent, version-controlled provisioning. Delivered an end-to-end POC for name matching using Google Vertex AI and Generative AI models (text-bison, text-unicorn, Gemini 1.0, 1.5 Pro, and 1.5 Flash) through synthetic data generation, prompt engineering, fine-tuning, and performance evaluation.
Education
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