AI Software Engineer-Planta Ford Irapuato

Ford, Inc; Irapuato; Hybrid; MXN 700,000 - 1,000,000; Full time

Job summary

The AI Software Engineer at Ford designs, builds, and maintains AI-enabled software for business and manufacturing use cases. You will work with AI Architects, Data Engineers and manufacturing teams to deliver scalable AI products, data pipelines, APIs, and predictive models.

You will contribute to deployment, monitoring and continuous improvement, supporting Industry 5.0 initiatives to transform operational data into actionable insights.

Qualifications

• BS degree in a relevant field with strong AI focus.
• Experience building cloud-based AI software.
• Proficiency in Python and ML frameworks.

Responsibilities

• Design, develop, implement and maintain AI-enabled software.
• Build ML pipelines, APIs and backend services.
• Deploy, monitor and improve AI models in prod.
• Collaborate with AI architects, data engineers and teams.

Skills

Python

ML concepts

APIs

Data preprocessing

Communication

Education

Bachelors in CS/AI

Tools

TensorFlow

PyTorch

FastAPI

Docker

Vertex AI

Job description

The AI Software Engineer is responsible for designing, developing, implementing, and maintaining AI-enabled software applications that support business and manufacturing operations. The position works closely with AI Architects, Data Engineers, Manufacturing Teams, and Digital Transformation leaders to build intelligent solutions using Machine Learning, Generative AI, cloud technologies, and enterprise data platforms. This role contributes to the development of scalable AI software products, data pipelines, APIs, and predictive models while supporting deployment, monitoring, and continuous improvement activities. The AI Software Engineer serves as a key contributor to Industry 5.0 and Industry 6.0 initiatives, helping transform operational data into actionable business insights through innovative AI-driven solutions.

AI Software Development

• Develop AI-enabled software applications and intelligent business solutions.
• Build and maintain Machine Learning and data processing pipelines.
• Develop APIs and backend services that support AI products and digital applications.
• Participate in software architecture implementation following engineering standards and best practices.

AI Model Development & Deployment

• Support the development, training, testing, and deployment of Machine Learning models.
• Assist in implementing Generative AI solutions and Large Language Model (LLM) use cases.
• Monitor model performance, accuracy, and reliability in production environments.
• Support MLOps processes including model deployment, monitoring, and lifecycle management.

Data Integration & Analytics

• Integrate manufacturing, operational, and enterprise data sources.
• Perform data preprocessing, cleansing, validation, and transformation activities.
• Maintain data quality, consistency, and accessibility across platforms.
• Support business intelligence, analytics, and dashboard development initiatives.

Collaboration & Continuous Improvement

• Collaborate with AI Architects, Data Engineers, Manufacturing Teams, and Business Stakeholders.
• Participate in Agile ceremonies, sprint planning, and technical reviews.
• Contribute to digital transformation and continuous improvement initiatives.
• Support troubleshooting, incident resolution, and software maintenance activities.

Innovation

• Research emerging AI technologies, frameworks, and industry trends.
• Support proof-of-concept (PoC) and pilot projects involving AI and advanced analytics.
• Recommend software, data, and process improvements that enhance operational performance.

Education

• Bachelor’s Degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science, or related field.
• Certifications in AI, Cloud Technologies, Data Engineering, or Software Development are a plus.

Experience

• 3+ years of experience in software development, Artificial Intelligence, Machine Learning, or related technical roles.
• Experience developing cloud-based applications and enterprise software solutions.
• Experience working with Python and AI/ML frameworks.
• Experience integrating APIs, databases, and cloud services.
• Basic understanding of DevOps and MLOps practices.
• Experience in manufacturing, Industry 5.0, or smart factory environments is preferred.

Technical Skills

Artificial Intelligence & Machine Learning

• Machine Learning Model Development.
• Deep Learning Fundamentals.
• Generative AI Concepts.
• Large Language Models (LLMs).
• Model Training and Evaluation.
• AI Solution Deployment and Monitoring.

Programming & Software Development

• Python Development.
• Object-Oriented Programming.
• REST API Development.
• Backend Software Engineering.
• Microservices Fundamentals.
• Software Development Lifecycle (SDLC).

Frameworks & Libraries

• TensorFlow.
• PyTorch.
• Scikit-learn.
• FastAPI.
• Pandas.
• NumPy.

Cloud & Data Platforms

• Google Cloud Platform (GCP).
• Vertex AI.
• BigQuery.
• SQL and NoSQL Databases.
• Cloud-Based Data Solutions.

DevOps & Tools

• GitHub / GitLab.
• Docker.
• CI/CD Tools.
• Power Platform.
• Qlik Sense or Data Visualization Tools.
• Agile Project Management Tools.

Leadership & Behavioral Competencies

• Problem Solving.
• EAffective Communication.
• Teamwork and Collaboration.
• Innovation Mindset.
• Continuous Learning.
• Accountability.
• Adaptability.
• Results Orientation.
• Customer Focus.
• Analytical Thinking.

Preferred Qualifications

• Experience implementing AI solutions in manufacturing environments.
• Knowledge of Industry 4.0 and Industry 5.0 concepts.
• Experience with Industrial IoT (IIoT) data integration.
• Exposure to MLOps and AI model lifecycle management.
• Working knowledge of Cloud AI platforms such as Vertex AI.
• Familiarity with Smart Manufacturing and Digital Transformation initiatives.

Key Success Metrics (KPIs)

AI Solution Delivery

• Number of AI solutions successfully deployed.
• Delivery performance against project milestones.
• AI application uptime and availability.

Technical Performance

• Model accuracy and reliability.
• Defect reduction and software quality improvements.
• API and application performance metrics.

Team & Operational Impact

• Sprint completion rate.
• User satisfaction and adoption levels.
• Incident response and resolution time.
• Contribution to digital transformation initiatives.

Business Impact

• Productivity improvements enabled by AI solutions.
• Data quality and integration eAectiveness.
• Support for smart manufacturing and operational optimization initiatives.

Position Value Proposition

The AI Software Engineer plays a critical role in transforming business and manufacturing operations through intelligent software solutions. By combining software engineering, Artificial Intelligence, cloud technologies, and analytics, this position helps accelerate digital transformation, improve operational efficiency, and enable the next generation of Smart Manufacturing and Industry 5.0 capabilities.