Research Engineer

General Analysis; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

General Analysis, based in San Francisco, is seeking a Research Engineer to lead efforts in post-training models and adversarial simulations. This role requires expertise in reinforcement learning and a solid understanding of the entire training pipeline.

The ideal candidate will be innovative and results-oriented, eager to engage with real-world AI security challenges while collaborating with a talented team.

Qualifications

• Comfortable with PyTorch, reinforcement learning techniques, and related infrastructure.
• Experience in advancing machine learning research and eager to learn.
• Publications in top-tier conferences like NeurIPS or ICML.

Responsibilities

• Responsible for post-training models for adversarial capabilities using RL.
• Work on the entire training pipeline from data generation to evaluations.
• Tackle engineering challenges in distributed systems and innovate methods.

Skills

PyTorch

Reinforcement Learning

Machine Learning Research

Technical Acumen

Tools

Tinker

verl

Job description

General Analysis is a security research lab focused on adversarial simulations, evaluations, and runtime protection.

We are based in San Francisco and work across research, engineering, and product.

About the role

As a Research Engineer, you will be responsible for post-training models for adversarial capabilities using reinforcement learning.

You will work with the entire training pipeline from data generation and environment design to evaluations.

You will tackle engineering challenges involving distributed systems, innovate new methods for data-constrained and low signal-to-noise environments, and make algorithmic improvements for applying trained models for adversarial simulations.

You may be a good fit if

• You are comfortable with PyTorch, RL infrastructure, post-training infrastructure, or tools such as Tinker and verl.
• You have academic and/or industry experience with reinforcement learning or machine learning research, or are eager to learn.
• You have publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ACL, or similar.
• You have security experience, or are excited to build it here.
• You have a high level of agency, strong technical acumen, and clarity of thought.

You'll thrive here if

• You are excited about applying novel research and new technology to real-world problems.
• You are excited to learn new domains and build deep context in AI security.
• You are results-oriented and can balance deep exploration with practical implementation.
• You proactively step outside defined boundaries to support the team's mission and unblock others.