At a Glance
- Tasks: Build AI-powered workflows and develop data-driven product capabilities using machine learning.
- Company: Join Kaseya, a leader in AI-powered IT management and cybersecurity software.
- Benefits: Competitive salary, growth opportunities, and a dynamic work environment.
- Other info: Mentorship opportunities and a culture of innovation and accountability.
- Why this job: Transform the IT industry with cutting-edge technology and impactful projects.
- Qualifications: 5+ years in machine learning engineering and experience with Python and data analysis tools.
About Kaseya
Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success. Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide. Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike. At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar.
Job Summary
We’re hiring a Staff Applied Machine Learning Engineer to build AI-powered workflows and data-driven product capabilities across Kaseya’s product suite. This role focuses on applied ML, data analysis, model development, and production integration of AI features that help classify requests, recommend actions, route work, enrich data, and automate repetitive workflows. You’ll partner with Product, Engineering, Data, and ML teams to deliver production-ready AI capabilities while helping teams adopt repeatable patterns for model evaluation, workflow design, and responsible AI usage.
Roles & Responsibilities
- Analyze product and customer data using Python, pandas, SQL, PySpark, or similar tools to identify patterns and modeling opportunities.
- Build and productionize ML models for classification, recommendations, similarity, ranking, routing, and prediction use cases.
- Design AI-powered workflows that transform unstructured inputs such as tickets, emails, forms, messages, and logs into structured data.
- Partner with Engineering teams to integrate ML models and AI workflows into production systems through APIs, services, and automation logic.
- Define evaluation methods, telemetry, feedback loops, and monitoring practices for AI-powered product features.
- Build reusable patterns, templates, and best practices for data ingestion, feature creation, model usage, and responsible AI implementation.
- Provide technical guidance to product teams on AI opportunity sizing, ML design, model trade-offs, and production readiness.
- Mentor junior data and ML engineers through code reviews, model reviews, pairing, and technical coaching.
Required Qualifications
- 5+ years of experience in data science, machine learning engineering, applied ML, or a related production-focused role.
- Experience building ML models for classification, recommendation, similarity, ranking, prediction, or related product use cases.
- Experience using Python, pandas, SQL, and PyTorch or similar tools for data analysis and model development.
- Experience using PySpark or similar distributed data processing frameworks.
- Experience integrating ML models into production systems through APIs, microservices, batch workflows, or automated product workflows.
Preferred Qualifications
- Experience with LLM-powered workflows, RAG, prompt engineering, fine-tuning, tool use, or agent orchestration.
- Experience building agent-assist features, automated resolution workflows, or AI-powered operational products.
- Experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar platforms.
- Experience with production model monitoring, model evaluation, online experiments, or feedback loops.
- Experience applying matrix factorization, embeddings, clustering, dimensionality reduction, or latent factor modeling.
- Experience working in a platform or enablement role supporting multiple product teams.
- Experience mentoring data scientists, ML engineers, analysts, or software engineers on applied ML practices.
Compensation Range
The base salary range for this job is CAD $220,000 - $280,000 / year. An individual’s base pay depends on various factors including geographical location and review of experience, knowledge, skills, and abilities of the applicant. At Kaseya, certain roles are eligible for benefits and additional rewards. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee’s role.
Additional Information
Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.
Staff Applied ML Engineer in Toronto employer: Kaseya
Kaseya is an exceptional employer located in Toronto, Ontario, offering a dynamic work culture that fosters innovation and accountability. Employees benefit from extensive growth opportunities within a high-performance environment, where their contributions directly impact the future of IT management and cybersecurity. With a commitment to leveraging cutting-edge technology and AI tools, Kaseya empowers its team members to excel in their roles while enjoying a collaborative atmosphere that values creativity and results.
