AI/ML Systems Engineer

Role overview

Responsibilities

• Define system requirements, interfaces, workflows, and diagnostic evidence requirements.
• Support AI-enabled issue detection, root-cause analysis, guided resolution, retrieval, decision support, and diagnostic reasoning.
• Collaborate across embedded systems, cloud platforms, data environments, and AI/ML technologies.
• Translate business and engineering needs into technical requirements for systems, APIs, workflows, and support tools.
• Evaluate AI performance and integrate containerized AI solutions into cloud environments and workflow systems.
• Define observability needs for metrics, traces, dashboards, alerts, logs, and escalation.
• Participate in integration, triage, investigations, testing, deployment, and improvement; communicate risks and trade-offs.

Required qualifications

• Bachelor’s degree in a relevant field such as computer science, engineering, AI, machine learning, robotics, or data science.
• Strong proficiency in Python; familiarity with software systems, AI/ML concepts, retrieval, inference, model evaluation, and data pipelines.
• Familiarity with APIs, Git-based development, containerized workflows, and AI/ML prototyping approaches.
• Interest in embedded systems, intelligent diagnostics, and software-driven products.
• Ability to structure ambiguous challenges, document requirements, and communicate with stakeholders.
• Experience building or prototyping AI/ML-enabled solutions through work, internships, research, or academic projects.

Preferred qualifications

• Relevant technical master’s degree preferred.
• Experience with LLMs, semantic retrieval, vector search, ranking, agent workflows, or decision-support systems preferred.
• Experience with PyTorch, TensorFlow, scikit-learn, LangChain, Vertex AI, or BigQuery preferred.
• Experience with chatbots, copilots, AI assistants, search, or reasoning systems preferred.
• Familiarity with AI evaluation, embedded systems, diagnostics, telemetry, cloud, Docker, GitHub, CI/CD, Dynatrace, or Grafana preferred.

Work schedule

• The description says hybrid work with onsite presence required four days per week.
• Candidates must be available to work onsite from the start; in-person interviews may be required.

Pay and employment

• Contract position based in Ottawa, Ontario.
• Pay range is CAD 50.00–67.00 per hour.

Workplace

• The description also labels the position fully onsite in Ottawa.