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Machine Learning Specialist – Cybersecurity Products

  • Montreal, QC, Canada

Full-time

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Job details

Job type
Full-time
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Experience
3+ years of experience in Machine Learning or AI development.
Posting language
English
Posted

Original job description

Company Description

StreamScan Cybersecurity is a Canadian company specializing in advanced cyber defense for organizations in defense, aerospace, and critical infrastructure. Since 2011, the company has focused on proactive threat detection and rapid incident response, powered by proprietary AI-driven technology. StreamScan operates a 24/7 Security Operations Center (SOC) and emphasizes close collaboration, transparency, and real-time reporting for clients. Its research center develops patented, state-of-the-art cybersecurity solutions that align with international standards. The team is composed of experienced, certified cybersecurity professionals dedicated to ensuring business continuity and maximum protection.

Role Description

We are looking for a highly motivated Machine Learning Specialist to help design and develop advanced cybersecurity solutions powered by Artificial Intelligence and Machine Learning. The successful candidate will work closely with cybersecurity researchers, software engineers, SOC analysts, and product teams to build intelligent detection and response capabilities for next-generation security platforms.

Key Responsibilities

  • Design, develop, train, and optimize machine learning models for cybersecurity applications.
  • Develop behavioral analytics and anomaly detection algorithms for endpoint, network, and cloud environments.
  • Build AI-powered detection engines for malware, ransomware, insider threats, account compromise, and advanced persistent threats (APTs).
  • Develop User and Entity Behavior Analytics (UEBA) capabilities.
  • Create automated threat classification, prioritization, and response mechanisms.
  • Process and analyze large volumes of telemetry data from endpoints, networks, cloud platforms, and security logs.
  • Collaborate with SOC and threat intelligence teams to improve detection accuracy and reduce false positives.
  • Evaluate and integrate emerging AI technologies, including Large Language Models (LLMs), Generative AI, and autonomous security agents.
  • Participate in product architecture and roadmap discussions for XDR, EDR, NDR, and MDR solutions.

Required Technical Skills

  • Machine Learning & AI
  • Strong knowledge of supervised, unsupervised, and reinforcement learning.
  • Experience with anomaly detection and clustering techniques.
  • Deep understanding of feature engineering and model optimization.
  • Experience with neural networks, deep learning, and transformer architectures.
  • Knowledge of explainable AI (XAI) and model interpretability.
  • Experience with LLMs, Retrieval-Augmented Generation (RAG), and AI agents.
  • Programming
  • Advanced Python development skills.
  • Experience with ML frameworks:
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • XGBoost
  • Experience developing APIs and microservices.
  • Data Engineering
  • Experience processing large-scale datasets.
  • Familiarity with:

*Apache Spark

*Kafka

*Vector databases

*Knowledge of MLOps practices and model lifecycle management.

Desired Qualifications

  • Master or PhD in Artificial Intelligence, Data Science, Cybersecurity, or related field.
  • 3+ years of experience in Machine Learning or AI development.
  • Experience working on cybersecurity products or security analytics platforms.
  • Familiarity with threat intelligence feeds and cyber threat datasets.

Nice-to-Have Skills

  • Experience developing EDR/XDR detection logic.
  • Malware classification using AI.
  • Network traffic analysis and NDR technologies.
  • Experience with graph analytics for attack-path detection.
  • Knowledge of adversarial machine learning.
  • Experience building AI-powered SOC automation capabilities.
More about this job

Responsibilities

Design, train, and optimize machine learning models and AI-powered detection capabilities for threats across endpoint, network, and cloud environments. Analyze large-scale security telemetry and collaborate with cybersecurity, SOC, threat intelligence, engineering, and product teams to improve detection, automate response, and shape security product roadmaps.

Requirements

The role seeks advanced Python development skills, strong knowledge of machine learning methods and deep learning, and experience with ML frameworks, APIs, microservices, large-scale data processing, and MLOps. Desired qualifications include a master's or PhD in a relevant field, at least three years of AI or machine learning development experience, and familiarity with cybersecurity products, threat intelligence, or security analytics.

Skills

  • Machine Learning
  • Artificial Intelligence
  • Cybersecurity
  • Python
  • Anomaly Detection
  • Behavioral Analytics
  • Deep Learning
  • Neural Networks
  • Transformer Architectures
  • Large Language Models
  • Retrieval-Augmented Generation
  • TensorFlow
  • PyTorch
  • Apache Spark
  • Kafka
  • MLOps

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Data & Analytics
  • Software
  • Security & Safety
  • Science & Research

Keywords

  • Machine Learning
  • Artificial Intelligence
  • Cybersecurity
  • Python
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Anomaly Detection
  • Clustering
  • Feature Engineering
  • Model Optimization
  • Neural Networks
  • Deep Learning
  • Transformer Architectures
  • Explainable AI
  • Large Language Models
  • Retrieval-Augmented Generation
  • AI Agents
  • TensorFlow
  • PyTorch
  • Scikit-Learn
  • XGBoost
  • APIs
  • Microservices
  • Apache Spark
  • Kafka
  • Vector Databases
  • MLOps
  • User and Entity Behavior Analytics
  • Extended Detection and Response

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