AI/ML Engineering Manager

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI/ML Engineering Manager in Canada.

This role is a senior leadership opportunity at the intersection of hands-on machine learning delivery, technical architecture, and team management within a cloud-native consulting environment. You will lead a high-performing team of ML engineers and architects while also staying deeply engaged in customer-facing technical work. The position combines strategic ownership of AI/ML engagements with responsibility for hiring, mentoring, and scaling a world-class engineering practice. You will guide end-to-end machine learning solutions, from data pipelines and model development to production deployment and monitoring. At the same time, you will shape architecture decisions, influence pre-sales engagements, and advise clients on building sustainable ML and GenAI systems. This is a highly impactful role for a leader who thrives in complex, fast-moving environments and enjoys balancing people leadership with deep technical contribution.

• Lead, hire, and develop a high-performing team of ML engineers and architects, setting a strong technical bar and ensuring continuous growth.
• Conduct structured performance management, including feedback, coaching, and career development discussions across the team.
• Oversee staffing alignment, ensuring team members are effectively allocated to projects that match their skills and development goals.
• Lead ML assessments for clients, evaluating infrastructure, data readiness, and ML maturity to deliver actionable recommendations.
• Define and drive architectural direction across engagements, ensuring scalable, production-grade ML and AI systems.
• Guide clients in designing and operating MLOps, LLMOps, and AI production systems with a focus on sustainability and governance.
• Support pre-sales activities by contributing technical expertise during scoping, solution design, and proposal development.
• Lead end-to-end delivery of ML engagements, ensuring technical quality, execution excellence, and client satisfaction.
• Serve as a senior technical authority and primary point of contact for key client engagements.
• Contribute to internal practice development by mentoring, building accelerators, and improving ML engineering standards.

Requirements:

• 10+ years of experience in machine learning or AI, including significant client-facing or consulting experience.
• Proven experience in people leadership, including hiring, performance management, and team development.
• Deep expertise in AWS ML and GenAI ecosystem, with strong ability to design and defend end-to-end ML architectures.
• Strong background across multiple ML domains such as NLP, computer vision, classical ML, time series, or generative AI.
• Hands-on experience designing and operating production ML systems, including MLOps and LLMOps practices.
• Expertise in foundation model adaptation, including fine-tuning (LoRA, QLoRA, PEFT), RLHF/DPO, and RAG-based systems.
• Strong understanding of agentic AI systems, multi-agent architectures, and human-in-the-loop workflows.
• Ability to operate in ambiguous, fast-paced environments and translate technical decisions into business impact.
• Experience working with enterprise stakeholders across both technical and executive levels.
• AWS certifications (Machine Learning Specialty or Solutions Architect Professional) are strong differentiators.
• Experience in responsible AI, model governance, and bias/fairness evaluation is highly valued.
• Strong communication skills with the ability to lead discussions, influence decisions, and mentor teams.

Benefits:

• 100% remote work flexibility across Canada and international teams.
• Competitive base salary ranging from CAD $152,000 to $234,000 per year.
• Bonus, equity, commissions, and performance-based incentives.
• Comprehensive medical insurance for employees and eligible dependents.
• Generous PTO, holidays, and flexible time-off policies.
• Annual learning and development stipend plus paid certifications and exams.
• Equipment, office, and technology stipends to support remote work.
• Access to a global engineering culture focused on innovation and collaboration.
• Structured professional development plans and peer recognition programs.