First seen by our source: 4 hours ago
Machine Learning Specialist – Cybersecurity Products
@ StreamScan Cybersecurity
Montréal, Quebec
Overview
StreamScan Cybersecurity is hiring a full-time Machine Learning Specialist to design and build AI-driven detection and response capabilities for its cybersecurity products. The work covers ML models, anomaly detection, UEBA and automated threat response across endpoint, network and cloud telemetry. Schedule.
Responsibilities:
- Design and train machine learning models for cybersecurity
- Build anomaly detection and behavioral analytics for endpoint, network and cloud
- Develop AI-powered detection for malware, ransomware and APTs
- Build UEBA and automated threat response
- Work with SOC and threat intelligence teams to cut false positives
Requirements summary:
- Strong supervised, unsupervised and reinforcement learning knowledge
- Advanced Python development skills
- Experience with TensorFlow, PyTorch, Scikit-learn or XGBoost
- Experience with large-scale data tools such as Spark and Kafka
- Master's or PhD preferred, 3+ years ML or AI experience preferred
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- Not provided
- First seen by our source
- 2026-11-14
- Source record updated
- 2026-11-14
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Education | Master’s degree (preferred), Doctorate (preferred) |
| Fields of study | Artificial Intelligence, Data Science, Cybersecurity |
Summary and details written by AI from the posting; the employer’s posting is the authority.
StreamScan Cybersecurity
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
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.
Journal
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