Daniel Hernandez

Machine Learning Engineer | Production ML Systems | MLOps | Backend Platforms

Bogota, Colombia (Open to Remote)

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Summary

Machine Learning Engineer building production-grade ML systems across computer vision, LLM-based architectures, and financial infrastructure. Experienced in end-to-end pipelines from feature engineering and model training to deployment, observability, and optimization.

Experience

Software Engineer (Payments Platform)
PayJoy
Aug 2025 - Present
Bogota, Colombia
  • Optimize payment service database queries and indexing across 2 critical retrieval flows, improving performance under production load.
  • Expand observability with 3 telemetry layers (Datadog APM, custom metrics, and alerting) to improve incident response.
  • Drive payment processor integration expected to reduce annual transaction costs by ~$1M.
Senior AI and Backend Engineer
Reshut Tech
Dec 2024 - May 2025
Miami, USA (Remote)
  • Led end-to-end computer vision systems across 2 model families in PyTorch (YOLOv7 and Detectron2).
  • Architected ML deployments on GCP with 3 delivery pillars: containerization, CI/CD, and service scaling.
  • Introduced monitoring and logging to improve reliability of production AI services.
Data Scientist
Dataplicada
Aug 2020 - Nov 2024
Miami, USA (Remote)
  • Designed and deployed a RAG system with LangChain and 2 LLMs (Llama3 and GPT-4).
  • Created Python ETL pipelines for 2 data modalities (structured and unstructured).
  • Scaled analytics capabilities used by 100+ enterprise clients.
Software Engineer Intern
Tesla, Inc.
Sep 2022 - Dec 2022 (Concurrent Internship)
Reno, NV
  • Engineered real-time Python ETL pipelines for manufacturing data.
  • Reduced adhesive waste by 20% by identifying line bottlenecks.
  • Implemented Kubernetes-based CI/CD with Docker and Jenkins across 3 stages (build, test, and release).

Technical Skills

Python, SQL, C++, PyTorch, XGBoost, Computer Vision, RAG, FastAPI, GCP, Datadog APM, CI/CD, Docker, Kubernetes, ETL.