Automotive ML Scientist — Cloud AI, APIs & Data Pipelines

Ford México; Ciudad de México; Sur place; MXN 600 000 - 1 200 000; Plein temps

Résumé du poste

Ford México is seeking a skilled machine learning engineer to design and deliver modular data products for scalable AI applications. You will clean and prepare data, train models, and explore advanced techniques for automotive use cases while ensuring memory and latency constraints are met.

You’ll build APIs and UIs using FastAPI, Streamlit, Dash, and Plotly, deploy with Docker/Kubernetes, and collaborate across global teams to translate insights into actionable recommendations.

Qualifications

• Bachelor’s or Master’s in CS, Engineering, Mathematics, or Science or equivalent practical experience.
• 2–4 years of experience designing, building, and improving ML systems.
• Strong Python skills with NumPy, Pandas, and scikit-learn; ability to write readable, testable code.
• Experience developing APIs or services with FastAPI or similar frameworks; interfaces with Streamlit or similar tools.
• Experience deploying ML workloads on Google Cloud Platform (Vertex AI, Cloud Run, BigQuery, etc.).
• Familiarity with Google’s ADK or comparable agent frameworks; willingness to learn.
• Comfort with Git and GitHub workflows; clear written and verbal communication.

Responsabilités

• Design and build modular, production-ready ML data products for scalable consumption.
• Analyze, clean, and prepare structured/unstructured data; run statistical analyses for models.
• Experiment with state-of-the-art models for automotive use cases under memory/latency constraints.
• Develop agentic applications using Google’s ADK; integrate with tools/data/workflows.
• Deploy REST APIs and interfaces using Docker/Kubernetes and web frameworks (Dash/Plotly/Streamlit).
• Collaborate with teams; communicate findings, trade-offs, and recommendations clearly.

Connaissances

Python

NumPy

Pandas

scikit-learn

APIs/ FastAPI

Git/GitHub

Docker

Kubernetes

Dash/Plotly/Streamlit

Formation

Bachelor’s orMaster’s in CS/Engineering/Math/Science

Outils

Docker

Kubernetes

FastAPI

Streamlit

Dash

Plotly

Git

Description du poste

Ford México is seeking a skilled machine learning engineer to design and deliver modular data products for scalable AI applications. You will clean and prepare data, train models, and explore advanced techniques for automotive use cases while ensuring memory and latency constraints are met.

You’ll build APIs and UIs using FastAPI, Streamlit, Dash, and Plotly, deploy with Docker/Kubernetes, and collaborate across global teams to translate insights into actionable recommendations.