Head of ML & Embedded AI for Rescue Tech

Toast; Vancouver; On-site; CAD 160,000 - 180,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

4 weeks paid vacation

Relocation support available

Employee ownership opportunities

Flexible work environment

Job summary

Toast is seeking a hands‑on Head of Machine Learning to lead the ML strategy, oversee end‑to‑end development, and solve embedded ML challenges for their public safety tech. The role focuses on production ML, data pipelines, and ML ops within a hardware‑integrated sonar product.

Ideal candidates have 5–10 years in ML, strong Python with PyTorch/Scikit‑learn, and demonstrated leadership in ML teams. Relocation to Vancouver is supported.

Qualifications

• Bachelor’s or Master’s degree in Engineering, CS, Mathematics, Physics, or related field.
• 5–10 years of experience in machine learning, AI, and software development.
• Proven track record leading machine learning teams and delivering quality products.
• Experience with embedded ML on hardware or IoT devices.
• Strong proficiency in Python, with PyTorch and Scikit‑learn experience.
• End‑to‑end ML project experience: data pipelines to deployment.
• Experience with Jira and cloud platforms (AWS/Azure).

Responsibilities

• Define and execute the ML strategy aligned with product and business goals.
• Lead design and evolution of ML architectures for production systems.
• Establish standards, best practices, and development processes for ML systems.
• Oversee ML model development, validation, deployment, and lifecycle management.
• Oversee signal processing pipelines and ML ops practices including versioning and monitoring.
• Collaborate with Product, Engineering, and leadership to define the AI roadmap.

Skills

Python

PyTorch

Scikit-learn

Team leadership

ML strategy

Data pipelines

Jira

Cloud platforms

Education

Bachelor's or Master's in Engineering/CS/Math/Physics

Tools

AWS

Azure

Jira

Job description

Toast is seeking a hands‑on Head of Machine Learning to lead the ML strategy, oversee end‑to‑end development, and solve embedded ML challenges for their public safety tech. The role focuses on production ML, data pipelines, and ML ops within a hardware‑integrated sonar product.

Ideal candidates have 5–10 years in ML, strong Python with PyTorch/Scikit‑learn, and demonstrated leadership in ML teams. Relocation to Vancouver is supported.