AI/ML Engineer

Ford Motor Company

AI/ML Engineer responsible for software applications in data analytics for smart mobility at Ford. Join our GDIA team to influence key business decisions with data expertise and insights.

Posted 7/17/2026full-timeDearborn • Missouri • 🇺🇸 United StatesMid-LevelSenior💰 $99,600 - $192,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in full-stack software engineering, with a strong focus on cloud platform development and deployment, utilizing modern programming languages and methodologies. Proficient in building scalable applications and integrating machine learning for data-driven insights.

Highest-signal resume keywords

Full-Stack Software EngineeringCloud Platform Development (GCP, Azure)Java Application DevelopmentInfrastructure as Code (Terraform)Machine Learning Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

JavaPythonSQLTest-Driven Development (TDD)REST-style MicroservicesBig DataData ProcessingML TrainingCI/CDDevSecOps

Tools & Technologies

Google Cloud PlatformSpring BootAngularReactDockerJenkinsApache AirflowSplunkGrafanaVertex AI

Industry Keywords

Software Development LifecycleCloud NativeData Insight & AnalyticsMachine Learning Operations (MLOps)Infrastructure & Operations

Tech Stack

Tools & technologies

AirflowAngularApacheAzureBigQueryCloudDockerGoogle Cloud PlatformGrafanaJavaJavaScriptJenkinsKubernetesMicroservicesMS SQL ServerMySQLPostgresPySparkPythonReactSplunkSpringSpring BootSpringBootSQLTerraformVue.js

About the role

Key responsibilities & impact

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.
Responsible for designing, developing, testing and maintaining software applications and products to meet customer needs both on-prem and cloud native.
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.

Requirements

What you’ll need

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, BigQuery, 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).
Application Development: REST-style microservices (Spring Boot, Cloud Run) and JavaScript-based UI frameworks (Angular, React, or Vue).
Cloud & Infrastructure:
GCP Architecture: Google Cloud Platform services including Cloud Run, Google Cloud Storage (GCS), Kubernetes Engine (GKE), Cloud SQL, Cloud IAM, and BigQuery.
Infrastructure & Operations: Infrastructure as Code (IaC), Terraform.
DevOps, Reliability & Security:
CI/CD & Containers: Jenkins, Tekton, GitHub Actions, Git/GitHub, Docker, Podman, Cloud Build and Deploy, and Artifact Registry.
Monitoring: Splunk, Dynatrace, Grafana, Apigee, and Cloud Logging.
DevSecOps: SonarQube, 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 CatBoost.
Pipelines & Workflows: Oozie workflows, Apache Airflow, and Astronomer.
Production Integration: Vertex AI Endpoints, Batch Inference, and Astronomer.

Benefits

Comp & perks

Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
Paid time off and the option to purchase additional vacation time