System Engineer

Job summary

Define and document system requirements, workflows, and technical specifications while supporting AI-powered vehicle diagnostics and observability solutions. Collaborate across embedded, cloud, data, and AI teams to design diagnostic workflows and contribute to integration, testing, validation, monitoring, and troubleshooting.

Job details

Hiring: AI/ML Systems Engineer – Vehicle Diagnostics & Observability Location: Kanata, Ontario, Canada (Hybrid - 4 Days Onsite) Employment Type: Contract (12 Months) About the Role Ford is seeking an AI/ML Systems Engineer to support its next-generation Vehicle Diagnostics & Observability initiative. In this role, you will work at the intersection of Artificial Intelligence, Machine Learning, Embedded Systems, Cloud Technologies, and Vehicle Diagnostics, helping build intelligent diagnostic solutions for software-defined vehicles. You will collaborate with cross-functional teams to define system requirements, support AI-powered diagnostic workflows, and develop solutions that improve fault detection, root-cause analysis, and vehicle serviceability. Key Responsibilities Define and document system requirements, workflows, and technical specifications. Support the development of AI-powered vehicle diagnostics and observability solutions. Work across embedded systems, cloud platforms, data pipelines, and AI/ML models. Assist in designing intelligent diagnostic and decision-support workflows. Support AI/ML capabilities including LLMs, retrieval-augmented generation (RAG), and knowledge retrieval systems. Participate in system integration, testing, validation, and troubleshooting activities. Collaborate with engineering, product, cloud, and AI teams to deliver scalable solutions. Contribute to observability, monitoring, and analytics requirements. Required Qualifications Bachelor's or Master's Degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Machine Learning, Systems Engineering, or a related field. 3-6 years of experience in AI/ML Engineering, Systems Engineering, Cloud Engineering, Embedded Software, or a related area. Strong proficiency in Python. Experience with Machine Learning, LLMs, AI workflows, and data pipelines. Familiarity with APIs, Git, Docker, containerized applications, and cloud technologies. Strong analytical, problem-solving, and communication skills. Preferred Skills Generative AI, LLMs, LangChain, RAG, Vector Databases TensorFlow, PyTorch, Scikit-Learn Google Cloud Platform (GCP) BigQuery, Vertex AI Embedded Systems or Vehicle Diagnostics CI/CD, GitHub, Docker Observability tools such as Dynatrace or Grafana

What you’ll do

Define and document system requirements, workflows, and technical specifications while supporting AI-powered vehicle diagnostics and observability solutions. Collaborate across embedded, cloud, data, and AI teams to design diagnostic workflows and contribute to integration, testing, validation, monitoring, and troubleshooting.

Requirements

A bachelor's or master's degree in a relevant technical field and 3–6 years of experience in AI/ML, systems, cloud, embedded software, or a related area are required. Candidates should have strong Python skills and experience with machine learning, LLMs, AI workflows, and data pipelines, plus familiarity with APIs, Git, Docker, and cloud technologies.

Listed skills

• Python · Preferred
• Machine learning · Preferred
• Embedded Systems · Preferred
• Git · Preferred
• Docker · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• Machine Learning
• Large Language Models
• Retrieval-Augmented Generation
• AI Workflows
• Data Pipelines
• Systems Engineering
• Embedded Systems
• Cloud Technologies
• APIs
• Git
• Docker
• Generative AI
• LangChain
• Vector Databases
• Vehicle Diagnostics

Job areas

• Technology
• Engineering
• Software
• Data & Analytics
• Manufacturing

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