As an MLOps Engineer, I specialize in streamlining machine learning operations to enhance the efficiency and scalability of data-driven projects. My role involves leveraging a robust tech stack, including AWS, EKS, ArgoCD/Events/Workflow, Kubeflow, and a variety of Python libraries for ML, to deploy, manage, and monitor machine learning models in production environments.Key Responsibilities:Cloud Infrastructure: Utilizing AWS to build and maintain scalable and secure cloud-based solutions.Container Orchestration: Implementing and managing Kubernetes clusters using EKS for efficient resource utilization and orchestration.CI/CD Pipelines: Developing and maintaining continuous integration and continuous deployment pipelines with ArgoCD/Events/Workflow to ensure seamless model deployment and updates.Machine Learning Operations: Using Kubeflow to streamline and automate machine learning workflows, from model training to deployment.Python Development: Writing efficient and scalable code with Python libraries for machine learning, ensuring robust model performance and integration.Collaboration: Working closely with data scientists, software engineers, and other stakeholders to align on project goals and deliverables.My expertise lies in bridging the gap between data science and operations, ensuring that machine learning models are production-ready and maintainable at scale.

As the first software developer at EdilGo, I spearheaded the development of an innovative SaaS platform connecting construction companies with suppliers of construction materials/services. My journey from creating a proof of concept to leading a team of talented developers has honed my skills in full stack development, leadership, and a tiny bit of machine learning.Role and Achievements: - Joined as the first programmer and quickly advanced to CTO. - Developed a proof of concept for a SaaS platform that connects construction companies with suppliers of construction materials. - Helped the team secure initial investment through a compelling proof of concept. - Transitioned the POC into a Minimum Viable Product (MVP) and successfully onboarded initial customers. - Managed and led a tech team of four skilled developers. - Gained hands-on experience in full stack development and machine learning.

In this period of time, I tried out the following business paths (in no particular order): created and launched an iOS app, applied for a Patent of a baby changing station with adjustable height and scale included, created an e-commerce of mexican craftsmanship, managed and eventually closed my father in law's fishing tackle shop and some other minor stuff.The soft skills and knowledge I acquired from making so many mistakes in this stage of my career are priceless. Most important of all, the realisation that to succeed in business you need to be part of a great team.

I worked at ULSA Noroeste as a professor for diverse Engineering classes. My main task though, was to develop and promote the course in Renewable Energy Engineering, which was successfully launched and is up and running today.

My role at Quimera consisted mainly on researching for the latest advances in clean technologies, making feasibility analysis for these technologies applied in different industries and directly contact clients, suppliers and partners of Quimera's Cluster in order to enhance the business network.

+ Use telemetric instruments to assist oil directed drilling+ Monitoring and supervision of drilling equipment use

Thesis work in designing of an automated machining process and its feasibility analysis.