Jash T.

About Jash T.

I’m a Computer Science & Engineering (Data Science) student at D.J. Sanghvi College of Engineering (DJSCE) who enjoys building systems that actually work.My core strength lies at the intersection of backend engineering, data systems, and applied machine learning. I work primarily with Python and Java, designing APIs, data pipelines, and scalable backends that are reliable, secure, and performance-focused.Over the past few years, I’ve gained hands-on experience across different environments- As a Backend Developer Apprentice at TechLabs, I worked on schema design, secure API development (JWT, RBAC), and backend architecture decisions aligned with real product constraints- Through cloud and systems work, I’ve designed AWS infrastructure (VPCs, EC2, S3, CloudFront, RDS) with a focus on availability, isolation, and scalability- I’ve also collaborated in open-source and team-driven environments, learning how to balance clean engineering with delivery timelines.Some projects I’ve built include- A cryptocurrency price prediction platform with a Flask inference API and a React-based analytics dashboard- A high-performance Java ML engine that embeds Python-trained models into a JVM application using ONNX, achieving sub-millisecond inference without REST overhead- PodVerse, a full-stack system for multilingual text-to-speech, voice cloning, and audio processing - combining Node.js, Python, ML models, and a React frontend.I take a practical, execution-first approach: understand the problem, design the system, optimize what matters, and ship something usable. Right now, I’m deepening my understanding of distributed systems and machine learning, with the goal of building backend infrastructure that can support intelligent, data-driven products at scale.I’m open to collaborating with engineering-driven teams, startups, or research-oriented projects where solid system design and real impact matter.

Experience

1. Lead Ml Engineer

   Omdena

   Dec 2025 — Present · NY, US

   Worked on CodeMode: Domain-Adapted Embeddings for Agentic Codebases, focusing on building high-quality datasets and pipelines for code embedding models in agent-based AI systems.Key Contributions- Led text chunking and Q&A dataset generation across multiple frameworks to create structured training data- Performed EDA to validate dataset quality prior to model fine-tuning- Developed 19+ end-to-end test cases and refactored pipelines, reducing processing time by 30–40% and improving deployment reliability.

Education

• SVKM's Shri Bhagubhai Mafatlal Polytechnic and College of Engineering

  Diploma, Computer Engineering

• Dwarkadas J. Sanghvi College of Engineering

  Bachelor of Technology - BTech, Computer Science and Engineering (Data Science)