Lead Machine Learning Engineer

In this role, you will act as a technical leader driving the design and delivery of advanced machine learning solutions for enterprise clients across multiple industries. You will shape end‑to‑end AI architectures on cloud platforms, translating complex business problems into scalable, production‑ready ML systems. The position combines hands‑on engineering with client‑facing consulting, requiring both deep technical expertise and strong communication skills.

You will guide project teams through the full lifecycle of delivery, from solution design and pre‑sales engagement to deployment and optimization. A key part of your impact will be defining technical standards, mentoring engineers, and building reusable frameworks that elevate delivery quality. This is a high‑ownership leadership role at the forefront of applied AI and cloud innovation.

• Lead the technical strategy across pre‑sales and delivery phases, designing ML solutions aligned with client business needs
• Architect and implement end‑to‑end machine learning systems on cloud platforms, particularly GCP, ensuring scalability and performance
• Build and maintain production‑grade MLOps pipelines using tools such as Terraform and Infrastructure‑as‑Code practices
• Develop, deploy, and optimize machine learning models, including GenAI, recommendation systems, and predictive analytics solutions
• Define and evolve engineering best practices, architectural standards, and delivery frameworks across the ML practice
• Lead client‑facing technical discussions, translating complex AI concepts into clear, business‑oriented solutions
• Mentor and coach junior and mid‑level engineers through code reviews, technical guidance, and career development support
• Drive internal initiatives such as reusable accelerators, frameworks, and tooling to improve delivery efficiency
• Ensure high standards of software engineering quality, including testing, CI/CD, and system reliability
• Collaborate with cross‑functional teams to ensure successful deployment and adoption of ML solutions

• 7+ years of experience in machine learning engineering, data science, or software engineering roles
• At least 2 years of leadership experience in a tech lead, project lead, or mentoring capacity
• Strong experience designing and deploying production‑grade ML systems on cloud platforms (GCP strongly preferred)
• Proficiency in Python for backend ML development, including clean architecture and software engineering best practices
• Strong experience with Infrastructure‑as‑Code tools such as Terraform and MLOps frameworks
• Solid understanding of REST APIs development using frameworks like Flask or FastAPI
• Strong SQL skills for complex data manipulation and analysis
• Excellent communication skills with ability to engage both technical and executive stakeholders
• Proven ability to mentor engineers and lead technical discussions in consulting or client‑facing environments
• Experience with MLOps tools (e.g., Kubeflow, Vertex AI Pipelines, MLflow) is a strong plus
• Exposure to GenAI systems, distributed computing, or cloud certifications is a bonus

• Competitive salary ranging from CAD $175,000 to $200,000
• Fully remote work across Canada with home office support
• 20 days of annual paid vacation plus public holidays
• Additional wellness, lifestyle, and personal days for flexibility and balance
• Comprehensive employer‑paid health, dental, and virtual medical benefits
• Retirement savings plan with employer matching after 3 months
• Paid certifications and access to professional learning platforms (e.g., Udemy Business)
• Annual budget for internet, phone, books, and learning resources
• Company‑provided Mac Book and equipment
• Regular off‑sites, team events, and collaboration opportunities