Kaseya

Kaseya provides integrated IT management and security solutions for MSPs and SMBs, enabling centralized IT operations, remote management, cybersecurity, and automation.

IT Services

Information Technology

1K-5K (3500)

Founded 2000

$567M raised

87 open positions

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Senior Staff Applied ML Engineer

3 weeks, 5 days ago

Canada

Lead

Machine Learning Engineer

Software Development

Apache Spark Feature Engineering Kubeflow LLM Microservices MLflow MLOps Pandas Python PyTorch SageMaker SQL Vertex AI

Apply Now

Kaseya

Kaseya provides integrated IT management and security solutions for MSPs and SMBs, enabling centralized IT operations, remote management, cybersecurity, and automation.

IT Services

1K-5K

Founded 2000

$567M raised

View All Jobs 87

Description

Partner with multiple product teams to identify, scope, and deliver AI opportunities across the product suite.
Analyze data and perform ML modeling to extract insights and support product features.
Design and productionize models for categorization, recommendations, similarity, prediction, and ranking tasks.
Build AI-driven ingest flows that convert unstructured inputs such as tickets, emails, forms, messages, and logs into structured data.
Develop workflows that auto-fill fields, request missing information, surface similar past items, and automate simple repetitive requests where appropriate.
Work with engineers to integrate ML models and workflows into production systems with monitoring, fallbacks, and guardrails.
Define reusable patterns, templates, and best practices for ingestion, feature creation, model usage, and evaluation.
Provide architecture and design guidance on data- and ML-heavy features as a technical lead.
Mentor junior data/ML engineers and analysts through code reviews, pairing, and coaching on metrics, evaluation, and reliability.
Help establish standards for experimentation, documentation, and responsible AI usage across teams.

Requirements

5+ years of experience in data science, ML engineering, or a similar applied role with a track record of shipping production data/ML features.
Strong Python skills and experience with pandas for data analysis.
Experience with PySpark or other distributed data processing frameworks.
Solid understanding of supervised learning, classification, matrix factorization, embeddings, latent factor models, feature engineering, and model evaluation.
Proficiency with PyTorch or a similar deep learning framework and related ML tooling.
Strong SQL skills and experience with modern data warehouses or data lakes.
Comfort working with APIs, microservices, and production ML integration, including performance and reliability considerations.
Experience as a technical lead or senior individual contributor across multiple teams or projects.
Ability to translate business problems into data/ML projects and explain tradeoffs to non-ML stakeholders.
Experience mentoring junior engineers or analysts and improving team practices such as reviews, testing, and monitoring.
Strong communication skills and ability to drive alignment across product, engineering, and operations.
Experience with LLMs and language-centric workflows such as RAG, prompt engineering, fine-tuning, and tool/agent orchestration, preferred.
Experience building agent-assist features or automated workflows in operational or customer-facing products, preferred.
Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex and with production model monitoring, preferred.
Prior experience in a platform or enablement role supporting many product teams with shared data and ML capabilities, preferred.

Benefits

Base salary range of $360,000 to $380,000 CAD.
Equal employment opportunity regardless of race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, disability, veteran status, marital status, or other protected characteristics.

Interested in this position?

Apply directly on the company website

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