We are recruiting an experienced Technical Program & Project Management Associate to join our team to support our client in the automotive industry. NOTE: Hybrid

RESPONSIBILITIES

- Detect, understand, diagnose, and resolve complex software and electronics issues quickly and accurately
- Work with a cross-functional team responsible for defining, integrating, and maturing intelligent diagnostic workflows that span embedded vehicle behavior, cloud-based observability, AI reasoning engines, and human support processes.
- Help define system-level requirements, interfaces, and workflows for End to End Software Diagnostics & Observability initiative
- Support development of AI-powered embedded vehicle diagnostics capabilities that improve issue detection, case intake quality, root-cause isolation, and guided repair
- Work across embedded, cloud, data, and AI/ML domains to connect vehicle diagnostics with intelligent reasoning and observability workflows
- Help translate business, service, and engineering needs into technical requirements for diagnostic systems, AI engines, APIs, workflow orchestration, and support tooling
- Support AI/ML driven capabilities such as case intake assistance, knowledge retrieval, diagnostic reasoning, decision support, validation, and orchestration
- Define and refine requirements for diagnostic evidence collection, including DTCs, PIDs, Freeze Frame data, logs, event traces, module state, and procedural outcomes
- Support design of systems that combine Ford engineering knowledge, diagnostics data, and AI reasoning to isolate likely root causes in embedded vehicle systems
- Participate in evaluation and validation of AI system behavior using diagnostic evidence, service data, engineering content,



and observability signals
- Work with internal teams and suppliers to integrate containerized AI solutions into cloud environments and workflow systems
- Help define observability requirements for diagnostic systems, including logs, metrics, traces, dashboards, alerts, and escalation workflows
- Participate in system integration, issue triage, root-cause analysis, and cross-functional technical problem solving
- Support rapid iteration, testing, and deployment of AI-enabled diagnostic capabilities into engineering and non-production environments
- Communicate technical tradeoffs, risks, and recommendations clearly to engineering teams, product teams, and leadership
- Work under the guidance of experienced engineers Gather and document user or business requirements, analyze current processes, and translate needs into functional specifications
- Understand or help document how systems and components fit together, including integrations, data flows, and technology choices
- Participate in the stages of system delivery, from requirements and design through development, testing, deployment, and maintenance
- Help define system requirements and ensure components work together to meet performance, reliability, and operational needs
- Help prioritize features, maintain a product backlog or roadmap,



and coordinate with stakeholders and development teams

REQUIRED SKILLS & QUALIFICATIONS

- Bachelor’s or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Artificial Intelligence, Machine Learning, Robotics, Data Science, or related field from an accredited university (or a WES-evaluated equivalent)
- 3-6 years of experience in AI/ML engineering, embedded software, systems engineering, cloud engineering, or related areas through internships, research, academic projects, or full time work
- Strong academic foundation in AI/ML engineering with practical familiarity in machine learning, LLMs, retrieval workflows, inference systems, model evaluation, and data pipelines
- Strong proficiency in Python
- Familiarity with AI/ML prototyping and engineering workflows, including training, inference, prompt-based systems, retrieval-augmented workflows, embeddings, ranking, or reasoning pipelines
- Familiarity with software engineering fundamentals, APIs, Git-based development, and containerized application workflows
- Interest in embedded systems, vehicle diagnostics, software-defined vehicles, and intelligent support workflows
- Ability to translate ambiguous problem statements into structured technical requirements and system behavior
- Strong written and verbal communication skills and requirements authoring with the ability to drive high level abstract conversations with leadership
- Demonstrated ability through coursework, research, internships, or projects to build or prototype AI/ML enabled systems
- Systems Development Life Cycle, Software Systems, Systems Engineering, Product Management, Systems Architecture

📌 Technical Program (Ottawa)
🏢 Meda Engineering & Technical Services
📍 Ottawa