Data Scientist (AI)

TL;DR

Data Scientist (AI): Building and optimizing agentic systems for cybersecurity with an accent on LLM post-training, reinforcement learning, and complex reasoning loops. Focus on developing scalable AI agents, benchmarking performance with statistical rigor, and integrating advanced machine learning models into production security workflows.

Location: Must be based in the USA

Salary: $120,000–$180,000 per year

Company

A global leader in cybersecurity providing an AI-native platform to stop breaches and protect modern organizations.

What you will do

• Develop and post-train LLMs and AI agents using supervised fine-tuning and reinforcement learning techniques.
• Design complex agentic workflows including planning, reasoning, tool calling, and memory management.
• Establish objective benchmarking criteria and evaluation pipelines for agentic systems.
• Collaborate with cybersecurity subject-matter experts to automate analyst procedures.
• Optimize prompts and inference performance for large-scale deployment.
• Research and prototype state-of-the-art methods in agentic planning and AI reliability.

Requirements

• Must be based in the USA
• PhD-level depth of understanding in modern machine learning research.
• Strong command of LLM training fundamentals including architecture, optimization, and scaling.
• Core expertise in reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO) and reward modeling.
• Experience building agentic systems with tool calling and retrieval capabilities.
• Fluency with PyTorch, GPUs, and the LLM training/serving stack (e.g., Hugging Face, vLLM).
• Strong reproducible research engineering skills using clean Python.

Nice to have

• Experience generating synthetic training data and task simulators.
• Familiarity with inference-time scaling and test-time compute.
• Knowledge of agent safety, guardrails, and failure analysis.
• Background or strong interest in the cybersecurity domain.

Culture & Benefits

• Competitive compensation and equity awards.
• Comprehensive physical and mental wellness programs.
• Paid parental and adoption leaves.
• Professional development opportunities for all levels.
• Inclusive culture with employee networks and volunteer opportunities.