Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world‑class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.
We are looking for a MLOps Engineer to join our team. You will participate in the development and maintenance of AI products for our clients. At Factored we are building a company that we all hold as our own, every single one of us. We need your skills to help take this rocketship to new heights and help create new opportunities for us. In return, you will be rewarded with an amazing team that supports you, rich culture,



shared success and the flexibility to work– from the comfort of your home.
Functional Responsibilities
- Deploy machine learning models to production environments using industry best practices.
- Design and implement automated workflows for model training, testing, and deployment.
- Manage and optimize the infrastructure supporting machine learning workloads.
- Establish monitoring systems for deployed models to ensure performance and reliability.
- Work closely with data scientists, software engineers, and cross‑functional teams to understand model requirements and business objectives.
- Ensure compliance with industry regulations and data protection standards.
- Stay informed about the latest advancements in MLOps and integrate relevant technologies and methodologies.
- Continuously optimize processes to enhance efficiency and reduce deployment times.

Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or

📌 Senior MLOps Engineer (Ciudad de México)
🏢 Factored
📍 Ciudad de México