AI Engineer

Ford Motor Company; Naucalpan de Juárez; Presencial; MXN 600.000 - 1.000.000; Jornada completa

Descripción de la vacante

Ford Motor Company is seeking a data and AI software engineer to help design, build, and deploy scalable ML models and AI-powered solutions. You will work with GenAI technologies on Google Cloud Platform, contributing to the AI/MLOps platform by building Python-based apps and RESTful APIs while following robust software engineering practices.

You will collaborate with senior developers and product managers to accelerate AI development, implement CI/CD/CT pipelines, and explore state-of-the-art

Formación

• Bachelor’s degree in Computer Science / Computer Engineering or similar technical discipline.
• 2+ years of experience with Python and Cloud Engineering / Services such as GCP Vertex AI and related services.
• Solid foundation in Machine Learning concepts and GenAI technologies, including LLMs.
• Experience with AI/ML workflow orchestration tools (Airflow, Kubeflow).
• Experience in DevSecOps using tools such as Tekton, SonarQube, Checkmarks.
• Experience with scripting languages (e.g., Bash, PowerShell).

Responsabilidades

• Contribute to development and maintenance of Python-based applications leveraging GenAI and ML models.
• Collaborate with Senior Developers, Tech Anchors, and Product Managers to scale the AI/MLOps platform on GCP.
• Write clean, testable code and participate in code reviews using Git.
• Assist in developing autonomous AI agents and deploying AI models into production.
• Develop and integrate RESTful APIs to connect systems within the ML platform.
• Automate model training, re-training, and deployment pipelines with Agile and CI/CD/CT.
• Work with the team to break down tasks, explore NLP, CV, MLOps, and Kubernetes, sharing learnings.

Conocimientos

Python

Cloud Engineering

GCP Vertex AI

LLMs

Airflow

Kubeflow

DevSecOps

Scripting

Educación

Bachelor’s degree in Computer Science / Computer Engineering or similar technical discipline

Herramientas

Docker

Kubernetes

Terraform

GitHub

Descripción del empleo

The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics.

In this role, you will be a core contributor to our internal AI Software Engineering and Data Science projects. Guided by Senior Developers and Tech Anchors, you will help design, build, and deploy scalable applications that consume machine learning models. You will get hands‑on experience deploying models on Google Cloud Platform (GCP), working with Generative AI technologies, and adhering to robust software engineering principles. This is an excellent opportunity for an engineer who is eager to accelerate their career in AI and DevSecOps.

• Contribute to the development and maintenance of Python-based applications that leverage GenAI, LLMs, and traditional machine learning models to solve business problems.
• Work closely with Senior Developers, Tech Anchors, and Product Managers to help deliver and scale our AI/MLOps platform on GCP for data scientists across the company.
• Write clean, testable, and maintainable code, actively participate in code reviews, and utilize GIT for version control and collaboration.
• Assist in the development of autonomous AI agents using frameworks such as LangGraph or ADK (Agentic Design Kit) to automate workflows.
• Support the deployment of AI models into production, run simulations for algorithm development, and collaborate on the design of intelligent systems.
• Develop and integrate RESTful APIs to connect various systems and services within the ML platform.
• Help automate AI model training, re‑training, and deployment pipelines by applying Agile methodologies and CI/CD/CT principles, under the guidance of senior engineers.
• Collaborate with the engineering team to understand the platform vision, break down tasks, and work together to solve complex Artificial Intelligence problems.
  Experiment with emerging technologies (NLP, Computer Vision, MLOps, Kubernetes) to continuously grow your own technical expertise and share new learnings with the team.
• Participate in innovating and standardizing AI/ML development practices within the team.
• Effectively leverage AI-powered development tools (such as GitHub Copilot, Cline, or Open Code) to accelerate software delivery while rigorously maintaining high standards for code quality, security, and performance.

Minimum Qualifications

• English proficiency (written and verbal)
• A Bachelor’s degree in Computer Science / Computer Engineering or similar technical discipline.
• 2+ years of experience with Python and Cloud Engineering / Services such as GCP Vertex AI and related services.
• A solid foundational understanding of Machine Learning concepts and Generative AI (GenAI) technologies, including Large Language Models (LLMs).
• Experience with AI/ML workflow orchestration tools: e.g., Airflow, Kubeflow etc.
• Experience in DevSecOps using tools such as Tekton, SonarQube, Checkmarks etc.
• Experience with scripting languages (e.g., Bash, PowerShell).

Desired Skills

• Masters in computer science / AI, Machine Learning or related field.
• Exposure to AI/ML workflow orchestration tools (e.g., Airflow, Kubeflow) and ML frameworks (Sklearn, TensorFlow, Pytorch).
• Familiarity with CI/CD concepts and tools like GitHub Actions, SonarQube, or Checkmarks.
• Basic knowledge or experience with Terraform.
• Contribute to the development of user interfaces for the ML platform using of React / Dash / Angular or similar frameworks.
• Experience working with container technology, docker files, docker images, GitHub, CI/CD concepts.
• Experience with Agile methodologies, Paired Programming, or Test-Driven Development (TDD).