Ankita Sharma

Professional Summary

Aspiring AI Engineer and Software Engineering Co-op Student with hands-on experience in machine learning systems, full-stack software development, and technical automation. Currently building expertise in PyTorch, local-first LLM architectures, and transformer-based interpretability, with a track record of delivering scalable software solutions.

Education

Technical Skills

AI & ML Frameworks: PyTorch, Hugging Face, TransformerLens, scikit-learn, Local Inference Runtimes

Languages: Python, Java, TypeScript, JavaScript, SQL, C, HTML/CSS

Frameworks & Technologies: React, Node.js, Flask, FastAPI, Docker

Developer Tools & Cloud: Git/GitHub Actions, Linux, Cloudflare, Jupyter Notebook, VS Code, AWS (Learning)

Featured Projects

• Architected a privacy-first personal AI assistant and custom language architecture designed to optimize local-first AI code synthesis.
• Integrated local LLM runtimes and streamlined token/inference execution pipelines for low-latency, secure performance.

• Built a mechanistic interpretability framework utilizing PyTorch and TransformerLens to extract internal model activations.
• Trained layer-wise linear probes on transformer residual streams to audit latent intent representations and build dynamic safety guardrails.

Work Experience

• Led the modernization of the Facilities Department intranet, collaborating with managers, senior leadership, and executives to gather requirements and improve usability.
• Served as a liaison between business stakeholders and technical teams, translating requirements into effective technical solutions.
• Developed automated Excel dashboards for capital and expense tracking using advanced formulas, dynamic charts, and integrated reporting visualizations.
• Built workflow automation solutions using Microsoft Power Automate and Excel, reducing manual effort and improving reporting consistency.
• Collaborated with multiple departments to manage stakeholder expectations and deliver projects within established timelines.

• Collaborate with student developers to research, design, and document open-source software solutions.
• Develop Python-based tools, reusable workflows, and technical documentation to support project development.
• Analyse software architectures and contribute technical recommendations for project design and implementation.
• Create reproducible development resources that improve contributor onboarding and team knowledge-sharing.