Staff Data Scientist

Proofpoint; Toronto; On-site; CAD 130,000 - 180,000; Full time

Job summary

A leading company in cybersecurity is seeking a Staff Data Scientist / ML Engineer to spearhead innovative AI solutions and machine learning initiatives. The role requires extensive experience, technical leadership, and a commitment to deploying scalable AI systems. You will work cross-functionally to drive impactful solutions in a dynamic and collaborative environment.

Qualifications

• 10+ years of experience in data science or machine learning.
• 3+ years in a technical leadership or managerial role.
• Hands-on experience with LLMs and GenAI frameworks.

Responsibilities

• Lead development of machine learning models and analytics solutions.
• Architect and oversee AI solutions through the full lifecycle.
• Champion AI/ML best practices and promote a data-driven culture.

Skills

Leadership

Mentorship

Python

Problem Solving

Collaboration

Education

PhD in Computer Science, Data Science, or related discipline

Master’s degree in Computer Science, Data Science, or related discipline

Tools

PyTorch

TensorFlow

Docker

Kubernetes

AWS

GCP

Azure

Job description

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Proofpoint is hiring a Staff Data Scientist / ML Engineer to lead multiple Data Science, GenAI, and AI Engineering initiatives. The ideal candidate will drive the development and deployment of innovative machine learning and generative AI solutions, working cross-functionally with DevOps, product, and data engineering teams. This leadership role requires deep technical expertise, hands-on implementation experience, and a strong vision for scalable AI systems that power real-world applications in cybersecurity.

Responsibilities

• Lead the development of machine learning models and advanced analytics solutions to solve complex business problems.
• Design and implement generative AI and large language model (LLM) applications, including fine-tuning and domain adaptation for cybersecurity use cases.
• Collaborate with engineering teams to build scalable and secure LLM-based systems (retrieval-augmented generation, prompt engineering, evaluation pipelines).
• Architect and lead AI solutions across full lifecycle—from experimentation to MLOps pipelines and production deployment.
• Design experiments and use statistical analysis to measure the impact of various business strategies.
• Oversee the deployment of machine learning and LLM models in production, ensuring performance, scalability, and responsible AI practices.
• Lead the development of model performance monitoring, observability, and continuous learning pipelines.
• Define technical direction for LLM and GenAI adoption, including benchmarking open-source and commercial models.
• Champion AI/ML best practices including model governance, reproducibility, and ethical AI considerations.
• Promote a data-driven and AI-forward culture within the organization and advocate for cutting-edge AI adoption across teams.
• Stay current with advancements in LLMs, GenAI, AI engineering, and emerging AI regulations.

Qualifications

Education

• PhD or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or related discipline.

Experience

• 10+ years of experience in data science or applied machine learning, with 3+ years in a technical leadership or managerial role.
• Proven track record of designing, developing, and deploying ML and GenAI solutions at scale.
• Hands-on experience working with LLMs (e.g., OpenAI, Anthropic, LLaMA, Mistral) and GenAI frameworks (e.g., LangChain, LlamaIndex, Hugging Face).
• Experience in cybersecurity or enterprise-scale threat detection systems is a strong plus.

Technical Skills

• Proficiency in Python and relevant ML/AI libraries (e.g., PyTorch, TensorFlow, Transformers, Scikit-learn).
• Strong grasp of LLM fine-tuning, prompt engineering, RAG pipelines, vector databases (e.g., FAISS, Pinecone), and inference optimization.
• Experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
• Solid understanding of MLOps principles including CI/CD for ML, feature stores, model versioning, and monitoring.
• Familiarity with privacy, security, and compliance considerations in deploying AI solutions.

Soft Skills

• Excellent leadership and mentorship skills, with a collaborative approach to cross-functional problem solving.
• Ability to communicate complex technical ideas to both technical and non-technical stakeholders.
• Strong innovation mindset, strategic thinking, and a passion for applying AI to impactful real-world problems.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!