Neval Cam
Software Engineer
Education
Stanford University
2017 - 2021
Bachelor of Science in Computer Science (Artificial Intelligence)
Relevant coursework: Artificial Intelligence, Deep Learning, Programming Abstractions in C++, Computer Organization Systems, Natural Language Processing, Linear Algebra & Differential Calculus, Design and Analysis of Algorithms, Practical Unix
University of Southern California
2024 - 2026
Master of Science in Computer Science (Artificial Intelligence)
Relevant coursework: Machine Learning, Artificial Intelligence, Deep Learning, Web Technologies, Applied Natural Language Processing
Work Experience
Siemens
May 2025 - August 2025
Machine Learning Engineer Intern
- Implemented a modular, production-grade ML pipeline in Python, covering feature engineering, data cleaning, and model training for manufacturing defect repairs
- Engineered advanced feature engineering steps, including text parsing and LLM embeddings for feature extraction, along with PCA-based dimensionality reduction and statistical feature selection for transformation and optimization
- Integrated pipeline with a FastAPI-based REST API, enabling secure, authenticated endpoints for execution, monitoring, and reporting
- Built reusable, configurable pipeline components with robust testing, logging, and YAML configuration for flexible deployment
- Collaborated cross-functionally with data scientists, software engineers, and 2 manufacturing SMEs to ensure scalability, maintainability, and alignment with business requirements
Meta
August 2021 - June 2024
Software Engineer
- Led iOS development for Instagram Account Protection as sole iOS Engineer for over 2 years. Promoted after one year by exceeding expectations and transitioned into a full-stack role by spearheading projects end-to-end
- Launched 30+ projects and features, each increasing protection and recovery rates by 2â15%, demonstrating advanced understanding of security and recovery methods
- Achieved over 5-10% increase in account recovery rates every half and an increase of over 2 million users recovering IG accounts every year with launched projects
- Accomplished $220kâ$300k yearly SMS cost savings by launching features reducing dependency on costly recovery methods
Meta
June 2020 - September 2020
Software Engineering Intern
- Developed features such as story stickers and highlight pinning for Instagram Stories platform working with Objective-C
- Collaborated with cross-functional teams to test and analyze feature performance, completing projects involving planning, execution, testing, and data analysis
Projects
Multi-Task Fine-Tuning of BERT
Built a multi-task learning framework using LoRA adapters, PCGrad, and Mixture-of-Experts to jointly fine-tune BERT on sentiment analysis, paraphrase detection, and semantic similarity. Achieved state-of-the-art results surpassing single-task baselines (91.6% accuracy on SST-2, 84.5% on QQP, 0.899 Pearson correlation on STS-B).
Sound Reconstruction from Brain EEG Responses to Music
Implemented and optimized deep learning models (CNN, RCNN, encoder-decoder, and Transformers) to reconstruct music stimuli from EEG signals, achieving a classification accuracy of 82.86% and cosine similarity of 0.80. Preprocessed and transformed EEG data into power spectral density and music stimuli into mel spectrogram representations, outperforming baseline results from reference study.