Data Scientist

Ford; Ciudad de México; On-site; MXN 700,000 - 1,000,000; Full time

Job summary

Ford of Mexico is seeking an experienced ML Engineer to design production-ready data products and deploy AI solutions at scale. You will work on automotive use cases, explore state-of-the-art models, and deploy APIs and user interfaces using modern frameworks. Collaboration across teams and locations is core to this role.

The position emphasizes Python, ML model development, and cloud deployment, with a focus on reliable, scalable AI across Ford operations in Mexico.

Qualifications

• Bachelor's or master's in CS/Engineering/Math/Science or equivalent.
• 2–4 years building ML systems and improving ML workflows.
• Strong Python with NumPy, Pandas, scikit-learn required.
• Experience APIs with FastAPI and UI tools (Streamlit/Dash/Plotly).
• Experience deploying ML on Google Cloud (Vertex AI, Cloud Run, BigQuery).
• Familiar with ADK or similar agent frameworks and Git/GitHub.
• Clear written and verbal communication and cross-team collaboration.

Responsibilities

• Design and build modular, production-ready ML data products at scale.
• Analyze and prepare data; run statistical analyses for models.
• Experiment with state-of-the-art models for automotive use cases.
• Develop agentic apps using Google's ADK and integrate with tools and data.
• Deploy REST APIs and UIs using Docker/Kubernetes; showcase results with Dash/Plotly/Streamlit.
• Collaborate via Git/GitHub; communicate findings to technical and non-technical partners.

Skills

Python

NumPy

Pandas

scikit-learn

API development

Git workflows

Communication

Collaboration

Education

Bachelor's or Master's in CS/Engineering/Math/Science

Tools

FastAPI

Dash

Plotly

Streamlit

Docker

Kubernetes

GitHub

Job description

Why Join Ford of Mexico?

Celebrating over 100 years of legacy in Mexico, we are more than just a business we are a vibrant, collaborative community of over 14,000 innovators shaping the global future of transportation. At Ford, we build what matters, grow where it counts, and drive progress with heart. Whether you are collaborating at our state-of-the-art Global Technology and Business Center (GTBC) or manufacturing iconic, award-winning vehicles in our world-class plants, you will find a culture evolving together, built on trust, passion, and shared purpose. Here, your work moves people forward, and your growth is personal. Join us, and lets build whats next together.

In this position...

Our Enterprise Analytics & AI team, focused on industrial systems, turns data into practical and reliable products that improve how Ford designs, builds, and operates vehicles. This role exists to bring statistical analysis, machine learning, and modern AI, including agentic applications, to real automotive and industrial challenges, taking ideas from exploration and prototyping through deployment and continuous improvement. Your work will help Ford make faster, better-informed decisions and deliver AI solutions that scale across the business.

What you'll do...

• Design and build modular, production-ready machine learning data products using robust coding practices, so they can be consumed at scale.

• Analyze, clean, and prepare structured and unstructured data, and perform statistical analysis on large datasets to power models and AI applications.

• Explore state-of-the-art models and techniques, and run machine learning experiments to train and evaluate solutions for automotive use cases, including models that meet memory and latency constraints.

• Develop agentic applications using Google's Agent Development Kit (ADK), integrating agents with tools, data, and application workflows.

• Deploy REST APIs and lightweight user interfaces using Docker and Kubernetes, and showcase machine learning, deep learning, and generative AI solutions through web frameworks such as Dash, Plotly, and Streamlit.

• Collaborate through Git and GitHub, including code review, and communicate findings, trade-offs, and recommendations clearly to technical and non-technical partners.

You'll have...

• A bachelor's or master's degree in Computer Science, Engineering, Mathematics, or Science, or equivalent practical experience.

• Typically 2 to 4 years of experience designing, building, and improving machine learning systems. Candidates who have built comparable skills through other paths are encouraged to apply.

• Strong Python skills with NumPy, Pandas, and scikit-learn, and the ability to write readable, testable, and maintainable code. Experience developing APIs or services with FastAPI or similar frameworks, and interfaces with Streamlit or similar tools.

• Experience selecting, training, and evaluating models, with an understanding of data preparation, validation, metrics, and common sources of bias or data leakage.

• Experience deploying or supporting data and AI workloads on Google Cloud Platform (e.g., Vertex AI, Cloud Run, Cloud Storage, BigQuery, Artifact Registry, Cloud Build, Cloud Logging and Monitoring, Secret Manager, IAM). You are not expected to have used every service.

• Familiarity with Google's Agent Development Kit (ADK) or comparable agent frameworks, and a willingness to learn.

• Comfort with Git and GitHub workflows (branching, pull requests, code review), plus clear written and verbal communication and a collaborative approach across teams and locations.

Even better, you may have...

• Experience with deep learning, natural language processing, generative AI, or retrieval-based applications, including vector search, search platforms, or unstructured data.

• Experience with Docker and container-based development, automated testing, dependency and environment management, CI/CD, production monitoring, data pipelines, distributed processing, or cloud-based analytics.

Ford of Mexico is committed to being an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, pregnancy, veteran status, or disability status.

We thank all candidates for their interest, but only those selected for an interview will be contacted.

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