Senior Machine Learning Engineer – Toronto, Canada | Visa + Salary Insights

📍 Location: ca

🏷 Type: Not specified

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Job Overview

This Senior-Level Machine Learning Engineer role focuses on building and deploying scalable AI systems within a high-impact financial technology environment. Based in Toronto, this position operates within a leading AI innovation hub, working on deep learning, generative AI, and large-scale data systems. The ideal candidate brings 5+ years of engineering experience, strong production-grade coding skills, and a proven ability to translate complex ML models into real-world applications that serve millions of users.

🌍 Work Eligibility & Location

This is a fully onsite role in Toronto, meaning candidates must either already have work authorization in Canada or secure it independently. Since visa sponsorship is not clearly stated, international applicants should verify eligibility before applying. The opportunity is best suited for candidates able to work within North American business hours and collaborate closely with in-office teams.

💰 Salary Intelligence

The compensation package is highly competitive within the Canadian AI market. With a base range of $170K–$250K CAD, this role sits in the top tier for machine learning engineering positions in Toronto. The inclusion of a temporary market premium indicates strong demand for this skill set. Combined with enterprise-scale impact and benefits, this is a financially attractive role for experienced ML engineers.

📊 Role Breakdown

This role blends machine learning engineering (40%), system architecture (25%), data pipeline integration (20%), and research-driven experimentation (15%). You will design and deploy scalable ML systems using technologies like PyTorch, TensorFlow, and JAX, ensuring production reliability across high-volume financial applications. A major focus is on building GenAI-powered solutions and optimizing them for real-world usage.

You will process multi-modal datasets including transaction data, text corpora, and conversational logs, applying advanced modeling techniques. Strong emphasis is placed on clean code, API design, and system efficiency. Collaboration with researchers and engineers means you will also translate experimental models into production systems. The role demands precision in both engineering scalability and model performance optimization.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a high-difficulty senior role requiring deep expertise across both machine learning theory and software engineering. Candidates must demonstrate the ability to ship production-grade systems, not just build models. With 5+ years of experience required and strong competition from global AI engineers, only candidates with proven impact in scalable ML deployments will stand out.

🚀 Career Impact

This role offers strong career acceleration in enterprise AI. Working on systems that impact millions of users provides measurable experience in large-scale ML deployment. The exposure to GenAI, financial data systems, and production infrastructure significantly enhances your positioning for future roles such as ML Architect or AI Lead.

📋 Key Responsibilities

You will architect and deploy machine learning systems that integrate with enterprise data platforms. Responsibilities include writing scalable and maintainable code, optimizing ML pipelines, and ensuring system reliability. You will work with large-scale datasets including financial transactions and text data, applying deep learning frameworks like PyTorch and TensorFlow.

Additionally, you will collaborate with cross-functional teams to translate research into production systems. A key part of the role involves designing APIs, improving system efficiency, and automating workflows. Continuous learning and contribution to cutting-edge AI solutions are essential expectations.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

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🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role was posted recently with a clear application deadline approaching, indicating high urgency. Given the salary range and seniority, competition is intense, especially from experienced ML engineers in North America. Early applications with strong, tailored resumes significantly improve your chances of progressing to interviews.

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✅ Job Source & Verification

This job listing is sourced directly from the official company careers portal, ensuring high source credibility. All compensation, responsibilities, and requirements reflect the original posting. Last updated: April 2026, making this a current and active opportunity for qualified candidates.