Open to opportunities

Shweta Wankhade

@shwetawankhade

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AI/ML Engineer specializing in LLMs, RAG, and deep learning for real-world impact.

India

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What I'm looking for

I’m looking for an AI/ML role where I can build LLM/RAG and deep-learning solutions in real systems—combining GenAI automation with MLOps. I want to grow through hands-on research and production-ready engineering impact.

I’m an AI/ML researcher and engineer focused on deep learning and interdisciplinary problem-solving, with a strong interest in GenAI applications that drive measurable innovation across domains. Through my internship work, I’ve applied data-driven approaches to predictive diagnostics, anomaly detection, and AI-enabled control optimization in EV vehicle control workflows.

I also build GenAI for embedded environments and design practical automation tools—such as Python-based fault detection utilities and optimized scheduling for PCB workflows—while ensuring quality through systematic validation. In my projects, I develop LLM-powered assistant capabilities for semiconductor engineers and advance VLSI power estimation and learning recommendation systems using modern ML and NLP techniques.

Experience

Work history, roles, and key accomplishments

Vehicle Controls Intern

Dorle Controls

Jul 2024 - Nov 2024 (4 months)

Integrated data-driven analysis into VCU development by using CAN/sensor pattern insights to support predictive diagnostics, anomaly detection, and AI-enabled control optimization. Collaborated on ML-based regression and classification estimators for improved torque prediction, subsystem health monitoring, and early detection of abnormal EV behavior.

Anomaly Detection Diagnostics Regression Models Classification Torque Prediction

Research and Design Intern

Melux Control Gears Pvt. Ltd

Jul 2024 - Nov 2024 (4 months)

Researched generative AI-powered automation for embedded systems and built Python-based data analysis and fault detection tools to reduce downtime and improve reliability. Designed optimized Round Robin scheduling for AutoClean Touch PCBs, improving efficiency by 40%, and supported quality assurance validations that reduced component defects by 20%.

Generative AI For Embedded Systems Data Analysis Fault Detection Round Robin Scheduling PCB Automation Quality Assurance Testing Reliability Engineering Data Validation