Senior Data Scientist (AI)

Location: Toronto, Canada — Remote

Company

hirify.global is a software product company focused on software supply chain management, open-source security, DevSecOps, and AI-powered software security.

What you will do

• Provide technical ownership and direction for applied AI and data science initiatives from concept through production.
• Build and deploy models for malicious-behavior detection, anomaly detection, fraud analysis, and security or product use cases.
• Design GenAI solutions using LLMs, embeddings, retrieval-augmented generation, structured outputs, tool use, and agentic workflows.
• Establish evaluation datasets, quality metrics, drift monitoring, and business-impact measurement practices.
• Partner with engineering and MLOps teams on scalable APIs, deployment, observability, model lifecycle management, performance, and reliability.
• Mentor data scientists, advise cross-functional stakeholders, and promote secure, ethical, and responsible AI practices.

Requirements

• 7+ years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.
• Strong Python skills and practical experience with Databricks, LLM APIs, scikit-learn, and large structured or unstructured datasets.
• Experience building and shipping ML or GenAI applications from prototype to internal or customer-facing workflows.
• Knowledge of modern LLM ecosystems, including OpenAI, Anthropic/Claude, Hugging Face, and open-weight models.
• Experience with prompting, context management, structured outputs, retrieval, tool use, and agentic workflows using LangGraph, LangChain, Semantic Kernel, or similar frameworks.
• Proficiency with Git, testing, code review, collaborative software development, and communicating technical decisions to technical and non-technical stakeholders.

Nice to have

• Deep MLOps experience with MLflow or comparable tools, reproducible pipelines, CI/CD, serving, and production monitoring.
• Experience with Databricks ML, AWS SageMaker, Azure ML, PySpark, or large-scale production data pipelines.
• Experience with AI architecture, reusable technical standards, observability, tracing, incident response, or model-drift detection.
• Knowledge of MCP, agent-tool integrations, LLM guardrails, AI security, and production safety practices.
• Experience applying AI to cybersecurity, fraud detection, anomaly detection, code analysis, threat intelligence, or software supply-chain security.

Culture & Benefits

• Remote work arrangement for the Toronto, Canada location.
• Opportunities to collaborate with product, engineering, security, research, data governance, and legal teams.
• Diversity and Inclusion Working Groups.
• Parental Leave Policy.
• Paid Volunteer Time Off.