Security Data Science Engineer

Job Category

Software Engineering

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We are seeking a talented and motivated Security Data Scientist / ML Engineer with experience deploying, monitoring, and maintaining machine learning systems in security domains to join our Security Engineering organization. In this role, you will collaborate closely with security engineers, product teams, and internal stakeholders to understand high-impact security problems, design detection and response solutions, and contribute to the development, release, and operation of models and AI agents that protect Salesforce  a senior technical contributor, you will directly impact the effectiveness of Salesforce’s real‑time threat detection and automated defense capabilities.

You will also play a key role in advancing our use of large language models (LLMs) and AI agents to accelerate security insight generation and response. By integrating LLMs with security telemetry and detection pipelines, you will help automate root cause analysis, generate contextual explanations, and enable autonomous or semi‑autonomous security actions.

• Design and Develop AI‑Driven Defense Systems: Build and deploy intelligent, data‑driven systems that utilize machine learning and AI agents to enable real‑time attack pattern identification, risk assessment, and proactive defense across Salesforce products and global infrastructure.
• Advance Agentic AI & LLM Capabilities: Lead the integration of Large Language Models (LLMs) and autonomous agents with security data pipelines. Focus on automating root cause analysis, generating contextual explanations for risks, and enabling autonomous or semi‑autonomous security actions.
• Operationalize Security Models: Oversee the end‑to‑end lifecycle—including development, release, monitoring, and operation—of ML models and AI agents to ensure they deliver high‑impact protection at scale.
• Automate Attack Simulation: Develop autonomous AI agents capable of executing complex security tasks, such as performing advanced data correlations, identifying specific attack patterns, conducting automated penetration testing, and analyzing security impacts.
• Transform Telemetry into Action: Engineer platforms that synthesize large‑scale security telemetry into actionable risk intelligence and automated decisions.
• Cross‑Functional
  
  Collaboration:
  
  Partner closely with security engineers, infrastructure teams, and product stakeholders to deeply understand the threat landscape and design solutions that address high‑priority security problems.
• Apply LLMs and Prompt Engineering: Automate generation of security insights, explanations, and response workflows from detections and anomalies.
• Continuously Improve Algorithmic Performance: Focus on detection, classification, and behavioral modeling in security and threat intelligence domains.
• Improve Team Effectiveness: Collaborate effectively with team members and suggest improvements to reduce time‑to‑detection and mature our security ML platform.

• Professional
  
  Experience:
  
  6+ years of industry experience with a demonstrated passion for crafting, analyzing, and deploying scalable machine learning solutions.
• Security Domain Expertise:
  Proven track record in machine learning engineering focused on security use cases, such as anomaly detection, malware classification, or behavioral modeling.
• ML Operations (MLOps) & Cloud:
  • Experience deploying, monitoring, and maintaining ML systems in cloud environments (AWS or GCP).
  • Consistent record of building ML products using…