AI​/ML Engineer

Creating the future of smart mobility requires the highly intelligent use of data, metrics, and analytics. That’s where you can make an impact as part of our Global Data Insight & Analytics (GDIA) team. We are the trusted advisers that enable Ford to clearly see business conditions, customer needs, and the competitive landscape. With our support, key decision-makers can act in meaningful, positive ways.

Join us and use your data expertise and analytical skills to drive evidence-based, timely decision-making.

Employees in this job function are responsible for designing, developing, testing and maintaining software applications and products to meet customer needs both on-prem and cloud native. They are involved in the entire software development lifecycle including designing software architecture, writing code, testing for quality and deploying the software to meet customer requirements. Full-stack software engineering roles, who can develop all components of software including user interface and server side also fall within this job function.

As an AI/ML Engineer, you will join the Product Team, collaborating closely with Product Managers, Product Designers, Data Scientists and fellow engineers to deliver impactful analytic solutions. In this role, you will take ownership of the full technical lifecycle, handling both the end-to-end development and the ongoing support and maintenance of these solutions.

You’ll work across the full-stack technologies to enable the highest priority work to be delivered. Within this highly collaborative environment, you will:

• Provide thought leadership across the greater Ford community
• Define, design, develop, and deploy applications/services
• Perform design review, code review and mentor junior team members
• Create proof-of-concepts to test business ideas with working software
• Use Agile principles and software craftmanship practices to sustainably and efficiently engineer software
• Collaborate with product managers, product designers, product owners, data scientists, and other software engineers to define product direction
• Integrate with other Ford systems and business processes to create new digital experiences
• Partner with software engineers and data scientists from other teams to build solutions with proven value

• 5+ years' experience in Software Engineering.
• Bachelor’s degree in computer science, computer engineering or a combination of education and equivalent experience.
• 1+ year experience with developing for and deploying to cloud platforms (e.g. GCP, PCF, Azure)
• Implement and optimize cloud services and tools (e.g. Terraform, Big Query, GCP)
• Build and maintain the foundational systems that power scalable, reliable, high-performance environments while also developing the intelligence layer that transforms data into actionable insights through machine learning. Develop internal frameworks, APIs, and developer tools using:
• Core Software Engineering:
• Languages & Methodologies: Java, Python, SQL (or similar major programming languages), and Test-Driven Development (TDD).
• GCP Architecture: Google Cloud Platform services including Cloud Run, Google Cloud Storage (GCS), Kubernetes Engine (GKE), Cloud SQL, Cloud IAM, and Big Query.
• Infrastructure & Operations: Infrastructure as Code (IaC), Terraform.
• Dev Ops, Reliability & Security:
• CI/CD & Containers: Jenkins, Tekton, Git Hub Actions, Git/Git Hub, Docker, Podman, Cloud Build and Deploy, and Artifact Registry.
• Monitoring: Splunk, Dynatrace, Grafana, Apigee, and Cloud Logging.
• Dev Sec Ops : Sonar Qube, Fossa, Cycode, and Checkmarx.
• Data Engineering & Machine Learning (MLOps):
• Data Processing & Databases: Big Data, PySpark, MS SQL Server, PostgreSQL, and MySQL.
• ML Training: Google Vertex AI (Studio, Training, Model Registry), XGBoost, and Cat Boost.
• Pipelines & Workflows: Oozie workflows, Apache Airflow, and Astronomer.
• Production Integration: Vertex AI Endpoints, Batch Inference, and Astronomer.

Bachelor’s degree in computer science, computer engineering or a combination of education and equivalent experience.

You may not check every box, or your experience may look a little different from what we've outlined, but…