cristhIAn

Hello, I'm

Cristhian Wiki

Machine Learning Engineer

Self-taught ML engineer from Peru, shipping deep learning systems from research to production — next up, grad school in deep learning and neuroscience.

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profile.py Python 3.12 
 
 
 
 TERMINAL  
 
 
 $  
 
  ✓ FastAPI APIs 
 
  ✓ ML models trained 
 
  ✓ AWS deployment 
 
  ✓ Production ready 
 
  Status: Shipping ML systems in production 
 
 
 
 
    
 
   
   
 
Who I am
 
About Me
 
 Cristhian Wiki 

Hi, I'm Cristhian Wiki, a passionate machine learning engineer and
        self-taught researcher from Peru. I am a PyTorch lover, very
        interested in the creation of novel neural network architectures
        (SOA), as well as their rapid implementation and accessibility
        (using MLOps tools).



My goal as a human being is to be able to change the world and make
        it a better place (using deep learning and lots of creativity). I
        love a good challenge, and I'm planning to pursue a Master's or PhD
        next, focused on deep learning and neuroscience.



Outside of work, you'll find me riding motorcycles, tinkering with
        cars, traveling whenever I can, and at the gym — but especially
        hanging out with my cats, who are pretty much my whole world.

 
 
 
 
“Any fool can write code that a computer understands. Good programmers write code that humans can understand.”
 — Martin Fowler 
 
“Nothing interferes with my concentration. You could put on an orgy in my office and I wouldn't look up. Well, maybe once.”
 — Isaac Asimov 
 
“Somewhere, something incredible is waiting to be known.”
 — Carl Sagan 
 
 
 
  
 
 
Career
 
Experience
 
     
  1.   
     
     
    Senior Machine Learning Engineer — Consultant
     Jun 2025 — Present · Lima, PE (Hybrid) 
     
    Seidor Analytics
     
       
    • Designed scalable data platforms and end-to-end ML systems for beverage-industry clients across LATAM (Koandina, Bodegas La Negrita, Arca Continental, Industrias San Miguel).
    • Built real-time data architectures (AWS Kinesis, Glue, Athena, AppSync) and end-to-end MLOps pipelines in Snowflake ML with Feature Store and Model Registry.
    • Led demand-forecasting models and BI dashboards (Streamlit, Power BI), while optimizing cloud costs via IaC (CDK/SAM).
      •  
     
     
  2.   
     
     
    Tech Lead
     Nov 2024 — Jun 2025 · Lima, PE (Hybrid) 
     
    Sokso
     
       
    • Led architectural design of the SMART 3.0 platform, setting technical standards and guiding backend/frontend teams.
    • Headed the ERP migration from SAP to NetSuite, coordinating critical data transfer and business-process redesign.
    • Managed AWS infrastructure (EC2, ECS, S3), CI/CD pipelines, and cost/performance optimization.
      •  
     
     
  3.   
     
     
    Full Stack Developer
     Nov 2023 — Nov 2024 · Lima, PE (Hybrid) 
     
    Sokso
     
       
    • Led frontend (Vue.js) improvements for the SMART 2.0 platform and strengthened cybersecurity standards across frontend/backend (.NET).
    • Contributed to SMART 3.0's initial build (Nest.js + Next.js) with a DevOps pipeline on AWS (ECS, S3, CI/CD).
    • Built ML pilots for price forecasting and customer-churn prediction using time series techniques (PyTorch, GCP).
      •  
     
     
  4.   
     
     
    Full Stack Developer specialized in AI
     Nov 2023 — Mar 2025 · New York, US (Remote, Part-time) 
     
    ArkRisk
     
       
    • Built a RAG system with memory and tool use (FastAPI, LangGraph, Ollama) integrating DeepSeek, Llama3, and Phi4, deployed on a GPU-backed AWS instance.
    • Shipped production LLM solutions (Hugging Face Inference Endpoints, custom PyTorch models on EC2) combined with OCR for insurance-policy digitization.
    • Developed RAG-based QA chatbots integrating OpenAI Assistants v2, plus a Next.js frontend consuming the FastAPI services.
      •  
     
     
    5.   
  
 
   
 
 
Academics
 
Education & Achievements
 
 
 
    
Education

  
 
 
    
Achievements

 
     
  •  2018 – 2023 
    Beca 18 – PRONABEC (scholarship for students with high academic performance)
     
  •  2018 – 2023 
    Top 5% – Faculty of Sciences, UNI
     
    •  
 
 
 
 
    
Certificates

  
 
 
    
Presentations

  
 
 
  
  
 
Toolbox
 
Tech Stack
 
 
 
AI & Generative AI
 
 Deep LearningLLMsAgentic AIRAGCNNsTime Series 
 
 
Frameworks
 
 PyTorchTensorFlowScikit-LearnXGBoost 
 
 
MLOps & Deployment
 
 FastAPIDockerCI/CDMLflowKubeflowModel Registry 
 
 
Data & Cloud
 
 PythonSQLSnowflakeSparkAWSAzureGCP 
 
 
 
 
  
 
 
Side projects
 
Projects
 
 
 
  
  
 
Blood Cells Detection System 🔬🩸
 
This work proposes a fast and inexpensive system for the recognition of 3 types of blood cells based on convolutional networks. Our DL model is characterized by having reduced inference times, and also ease of deployment in hardware with reduced resources such as a Raspberry Pi.
 
 PytorchFlaskRaspberry 
 
 
Case Study
 
Live Demo
 
Source
 
 
 
 
  
  
 
Medical Chatbot Unimedic 🤖💬
 
Unimedic is a chatbot capable of responding to different medical queries in real time. It also performs segmentation of medical images (especially brain images) using Deep Learning models, and then provides some recommendations.
 
 PytorchFastAPIReact Native 
 
 
Case Study
 
Live Demo
 
Source
 
 
 
 
      
 
  
 
 
Get in touch
 
Let's build something
 

Open to interesting ML/AI conversations, collaborations, or opportunities.
      Reach out directly:

 
     
Email Me
    
LinkedIn
    
GitHub