Hi! I'm Gabrielly, but you can call me Kimi 🧩
I'm an ML Engineer focused on MLOps and AI Infrastructure with 2 years of experience. I build production AI systems that scale and cost less.
I'm currently building Billink AI — a SaaS platform that automates cloud and AI infrastructure cost auditing using multi-agent LLM pipelines.
What it does:
- Analyzes billing data from AWS, OpenAI, and Anthropic
- Identifies waste patterns (idle GPUs, expensive model overuse, storage inefficiencies)
- Generates actionable recommendations with projected savings
Roadmap:
- ✅ Architecture designed (3-stage agent pipeline: Extractor → Analyst → Advisor)
- 🚧 MVP in development (CSV upload → analysis → PDF report)
- 🎯 Goal: 2 paying customers for validation
Follow the journey: I share progress, learnings, and challenges on LinkedIn.
👩💻 Currently, I am...
- 💼 ML Engineer / MLOps Engineer at Cortex: Architected an Agentic AI system processing 80K+ stores across 700+ malls on Kubernetes, enabling a $2M revenue product line. Implemented monitoring, alerting, and batch inference pipelines.
- 🤖 AI Researcher at UFPI: Building hybrid BiLSTM-Transformer models for hate speech detection with feedback loop for retraining. Fine-Tune Baseline | BiLSTM Baseline
🛠️ Tech Stack
- MLOps & Infrastructure: Kubernetes (EKS), Karpenter, Spot Instances, Docker, MLflow, CI/CD for ML, Model Monitoring, Drift Detection
- Cloud: AWS (S3, Lambda, EC2, EKS, DynamoDB, Cost Explorer), Terraform, FinOps
- Machine Learning: LLMs, Agentic AI, RAG, NLP, TensorFlow, PyTorch, Physics-Informed ML
- Data Engineering: PostgreSQL, ClickHouse, Supabase, ETL/Data Pipelines, Analytics Engineering
- Observability: Grafana, CloudWatch, HyperDX (P95 Latency, Error Budgeting)
- Programming: Python, SQL, PySpark
✨ Highlights
- 🏆 Transpetro/Petrobras Hackathon (7th place): Physics-Informed ML for industrial prediction — identified $1.89M in fuel savings and 1,198 tons CO2 avoided. Paper | Dashboard | Model | REST API
- 🇧🇷 I Speak Kanoê: Built the first dataset for Kanoê indigenous language preservation. Documentation | Dataset
- 📊 Social Impact: Created Water Inequality Dataset of NE Brazil and published peer-reviewed research. Paper | GitHub
- 📊 Cloud Infrastructure Analyst (Freelance): Audited infrastructure handling 3.26B requests with 99.92% availability during Black Friday, analyzing EKS cluster efficiency and Spot Instance resilience.
🎖️ Certifications
- Stanford & DeepLearning.ai: Machine Learning Specialization. ML Project
- Harvard Aspire Institute: AI-Integrated Leadership Program (AILP) Alumna
- DataCamp: AI Engineer Associate & Data Engineer Associate
📚 My "Stanford Roadmap"
- As a neurodivergent learner, I thrive on structure and depth. I am executing a rigorous, self-directed curriculum based on Stanford University's Computer Science BS parallel to my formal degree.
📐 Click to see my full progress & Curriculum
Current Phase: Year 1 - Solid Foundation 🏗️ Focus: Mathematical rigor and algorithmic thinking.
Semester 1: Foundation (From November/25 to May/26)
- CS106A: Programming Methodology. Activities
- Introduction to Mathematical Thinking (In Progress)
- Introduction to Logic (In Progress)
- CS103: Mathematical Foundations of Computing
- CS106B: Programming Abstractions (In Progress)
Semester 2: Foundation II (From June/26 to December/26)
- PHYSICS61: Mechanics
- MATH19: Calculus I
- CS107: Computer Organization & Systems
- CS125: Data & Society
- CS109: Probability for Computer Scientists
- 🚧 Capstone Project 1
Year 2: Advanced Core 🚀
Semester 3 (From January/27 to June/27)
- MATH20: Calculus II
- MATH51: Linear Algebra & Multivariable Calculus
- CS111: Operating Systems Principles
- CS221: Artificial Intelligence: Principles and Techniques
Semester 4 (From July/27 to December/27)
- CS229: Machine Learning
- CS161: Design & Analysis of Algorithms
- CS205L: Continuous Mathematical Methods with an Emphasis on Machine Learning
- 🚧 Capstone Project 2
Semester 5: Specialization & Quantum 🕵🏼
Semester 5 (From January/28 to June/28)
- CS22N: Natural Language Processing with Deep Learning
- CS259: Algorithms Fairness
- PHYSICS71: Quantum
- 🚧 Capstone Project 3
🌍 Leadership & Volunteering
- 🧑🏫 Teaching Fellow: Data and AI for Social Analysis course at UFPI
- 🧑🏫 AI Instructor: Teaching AI for women entering tech at NGO
- 🇺🇳 United Nations MGCY: Major Group for Children and Youth volunteer
💬 Let's connect
- 💼 LinkedIn: Gabrielly Gomes
- 📧 Email: gabrielly.gomes@billinkai.com