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.

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).

Ford Motor Company is an Equal Opportunity Employer, as we are committed with a diverse workforce, and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran and basis of disability.

• 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.