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Chris Dsilva

Berlin, Germany

Chris Dolton Dsilva

AI/ML Engineering · Cloud (AWS) · AI Product & QA

MSc AI student in Berlin building applied ML systems — from multimodal RAG pipelines to AI product QA.

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Chris Dolton Dsilva

About

Building applied AI systems with rigor

A quick look at my background, what I'm studying, and what I'm focused on right now.

AI/ML Engineering student in Berlin (MSc Artificial Intelligence, Berlin School of Business & Innovation, in partnership with University for the Creative Arts) with hands-on experience across AI product QA, machine learning, and cloud-adjacent data engineering. Built and deployed a multimodal Retrieval-Augmented Generation (RAG) system with region-aware regulatory logic across Germany and Norway, improving retrieval accuracy from 76% to 86%. Currently pursuing AWS Certified Machine Learning Engineer – Associate, with practical grounding in GDPR and the EU AI Act. Seeking a Werkstudent role in AI/ML Engineering, Cloud, or AI Product/QA in Berlin.

Education

  • MSc Artificial Intelligence — Expected August 2027

Current Focus

  • Knowledge-graph-based retrieval (KG-RAG) as an MSc research extension
  • AI product QA workflows for regulated, trust-sensitive products

Research Interests

  • Retrieval-Augmented Generation & multimodal AI systems
  • Region-aware regulatory reasoning (GDPR, EU AI Act)
  • Model explainability and evaluation (faithfulness, hallucination rate)

Experience

Where I've worked

Internships spanning AI product QA, frontend engineering, and applied machine learning.

  1. AI Product Development & QA Intern

    Generation iTrust: wertvoll.sein

    Jan 2026 – Mar 2026Berlin, Germany
    • Validated AI-based matching logic by designing structured test cases and QA workflows, resulting in documented accuracy and reliability improvements adopted by the product team
    • Identified usability gaps in user flows by conducting functional and platform testing, delivering actionable feedback that shaped agile sprint priorities
    • Operated within an agile QA process end-to-end, strengthening cross-functional collaboration between engineering and product

  2. Frontend Web Developer

    Generation iTrust: wertvoll.sein

    Jul 2025 – Aug 2025Berlin, Germany
    • Built responsive, API-integrated interfaces by collaborating directly with backend engineers and designers, shipping a fully functional MVP

  3. Machine Learning Intern

    Cloud Counselage Pvt. Ltd.

    Sep 2024 – Jan 2025Mumbai, India
    • Analyzed the relationship between economic background and academic performance/outcomes across a multi-attribute student dataset, using data analysis to surface actionable demographic and participation trends

  4. Machine Learning Intern

    NullClass

    Dec 2023 – Feb 2024Remote
    • Contributed to applied machine learning tasks as part of a structured internship program, building on foundational data science and modeling skills

  5. Data Science & Machine Learning Intern

    Multiple Organizations (InternPe, CodSoft, Prodigy InfoTech, Bharat Intern, CodeClause, Oasis Infobyte)

    Feb 2023 – Nov 2023Mumbai, India
    • Completed a series of short-form data science and ML internships across six organizations as a deliberate early-career skills sprint before starting an MSc

Projects

Selected work

Applied AI and ML projects — from a research-grade RAG assistant to full-stack builds.

Portfolio / MSc Research Project · Ongoing

Regulation-Aware Multimodal Plant-Disease Assistant

A multimodal AI assistant combining vision-based plant-disease detection with Retrieval-Augmented Generation (RAG), improving held-out retrieval accuracy from 76% to 86% through domain-specific embedding fine-tuning.

  • Deployed a Streamlit conversational interface with region-aware regulatory logic spanning Germany and Norway, including image upload, multi-turn context persistence, and grounded abstention behavior to prevent unsafe recommendations
  • Designing an ongoing knowledge-graph-based retrieval comparison (KG-RAG vs. document RAG) as an MSc research extension, with an evaluation framework covering region correctness, faithfulness, and hallucination rate
PythonRAGStreamlitComputer VisionEmbedding Fine-tuning
GitHub

Bachelor's Major Project · Nov 2023 – May 2024

Image Colorization Using Generative Adversarial Networks (GANs)

A Conditional GAN with a U-Net generator architecture to automatically colorize black-and-white images, applying generative deep learning techniques end-to-end in PyTorch and Fastai.

  • Implemented and trained the full generator–discriminator adversarial pipeline from scratch, translating GAN theory into a working computer vision system
PyTorchFastaiGANsU-NetComputer Vision

Bachelor's Team Project — Team Lead · Jan 2023 – May 2023

Attendance System Using Facial Recognition

An automated attendance system using OpenCV, Haar Cascade detection, and an LBPH classifier, replacing manual attendance tracking with real-time facial recognition.

  • Directed development of a Tkinter-based interface for face capture and attendance-report generation, coordinating the team's build across detection, classification, and reporting components
OpenCVHaar CascadeLBPHTkinterPython
GitHub

Bachelor's Project · Jan 2022 – Apr 2022

HobbyMeet — Content-Based Recommendation Platform

A Flask web platform connecting users by shared hobbies and interests, including a content-based recommender system using TF-IDF vectorization and cosine similarity to match user interest profiles.

  • Designed the full-stack implementation end-to-end (HTML, CSS, Flask, Python), from recommendation logic through frontend delivery
FlaskPythonTF-IDFRecommender SystemsHTML/CSS

Skills

Tools & technologies

Grounded in Python and applied ML, with hands-on exposure to cloud, product QA, and AI governance.

Programming

Python

Machine Learning

Machine LearningPyTorchGenerative Adversarial Networks (GANs)Computer Vision (OpenCV)SHAP / Model ExplainabilityRecommender Systems

AI

Retrieval-Augmented Generation (RAG)GDPREU AI Act

Cloud

Cloud Computing (AWS)DatabricksPySpark

Backend

FlaskData Engineering

Frontend

Streamlit

Developer Tools

Power BIAgile / ScrumProduct QA & Usability Testing

Education

Academic background

  1. MSc Artificial Intelligence

    Berlin School of Business & Innovation (BSBI), in partnership with University for the Creative Arts (UCA)

    Expected August 2027Berlin, Germany

  2. BE Computer Engineering

    Fr. Conceicao Rodrigues College of Engineering (University of Mumbai)

    Jul 2020 – May 2024Mumbai, India

Certifications

Certifications & credentials

Applied Python Data Engineering Specialization

Data Analytics and Visualization

Virtual Experience

Complete Guide to Power BI for Data Analysts

Microsoft Press

Contact

Let's work together

Open to Werkstudent roles in AI/ML Engineering, Cloud, or AI Product/QA in Berlin. Feel free to reach out.

dsilvachris517@gmail.comgithub.com/dsilvachrisLinkedIn Profile
Berlin, Germany
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