Ford GDIA

Role: ML Engineer (GCP / Vertex AI / Agentic AI)
Location: Remote – All LATAM
Time Zone: US Central Time
Max Rate: $36/hr
Equipment: Vendor will provide laptop
Duration: 6 months +
Target Start Date: 9/14

Job Description

Role Summary
Ford GDIA is seeking a hands-on Machine Learning Engineer to join a newly formed AI delivery team focused on building and operationalizing Agentic AI solutions that support quality engineering and enterprise problem-solving workflows. This role will work closely with business stakeholders, data scientists, and software engineers to develop production-ready AI applications using GCP technologies including Vertex AI, Gemini, BigQuery, RAG frameworks, and AI Agents.

Responsibilities

• Design, develop, and deploy production AI applications using Vertex AI, Gemini, and related GCP services.

• Build Agentic AI solutions capable of reasoning, retrieval, decision-making, and multi-step workflow execution.

• Develop and optimize Retrieval-Augmented Generation (RAG) architectures using structured and unstructured data sources.

• Create AI agents that interact with enterprise data platforms, including BigQuery.

• Build APIs and backend services that support AI-powered applications and integrations.

• Collaborate with business stakeholders to translate requirements into scalable AI solutions.

• Implement monitoring, observability, evaluation, governance, and operational support for deployed AI systems.

• Integrate AI solutions into existing enterprise systems, platforms, and workflows.

• Support AI initiatives from proof-of-concept through production deployment and ongoing optimization.

Required Qualifications

• 5+ years of experience in Machine Learning Engineering, AI Engineering, or related disciplines.

• Proven experience building and deploying production-grade machine learning or AI applications.

• Strong hands-on experience with Google Cloud Platform (GCP).

• Experience working with Vertex AI and enterprise-scale AI/ML solutions.

• Experience developing LLM-based and Generative AI applications.

• Strong understanding of prompt engineering techniques.

• Experience building RAG pipelines and AI-powered retrieval/search solutions.

• Strong Python development experience.

• Experience integrating with enterprise data systems and APIs.

• Strong communication skills with both technical and non-technical stakeholders.

Nice-to-Haves

• BigQuery

• Gemini

• LangChain

• LangGraph

• Multi-Agent Architectures

• Vector Databases

• FastAPI, Flask, or similar backend frameworks

• CI/CD pipeline development

• Terraform and Infrastructure-as-Code practices

• GitHub Actions, Jenkins, or other DevOps tooling

• MLOps practices including model monitoring, evaluation, and governance

• Recommendation or personalization systems

• Intelligent workflow automation solutions

Why This Role
This is an opportunity to help establish and scale a new AI delivery capability within Ford GDIA. The engineer will work on cutting-edge Agentic AI and Generative AI initiatives, developing production solutions that deliver business impact while leveraging the latest advancements in Vertex AI, Gemini, and enterprise AI architectures.