---
title: 'Member of Technical Staff, Security Engineering at METR'
canonical: 'https://feeny.ai/job/member-of-technical-staff-security-engineering-metr-berkeley-w44zdwnsrdma'
type: 'job'
last_seen: '2026-09-07'
---

# Member of Technical Staff, Security Engineering at METR

- **Company:** METR
- **Location:** Berkeley, CA
- **Compensation:** $328k–$579k
- **Work type:** hybrid
- **Posted:** 2026-07-08
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/metr/775fa999-229d-40c1-b5eb-53794c20ee60

## Job description

## About METR

We are a nonprofit research organization that develops scientific methods to assess AI capabilities, risks, and mitigations, with a specific focus on threats related to AI R&D automation and misalignment. We believe it is robustly good for policymakers and civil society to have a clear understanding of risks from AI systems, and we are extremely excited to build a team of ambitious, excellent people to tackle one of the most important challenges of our time.

## About the role

Security at METR is becoming its own dedicated team, and you would be one of its first hires. It is extremely important that we continue to be an organization that frontier AI labs, governments, and the public trust with sensitive model access and confidential information. As misalignment incidents become more extreme and confidential information about models and frontier AI labs becomes more valuable, we expect to be under increasingly heavy pressure.

For us, security encompasses managing endpoints and securing development environments, cloud platform security, safely sandboxing agents and evaluations, VPN and VPC networking, application code reviews, account provisioning and access control, and helping ensure we use the best practices across all of our workflows.

What this role looks like

- Offensive security: You would be the first person on the team with an offensive security background. You'll run targeted red-team exercises against our own systems and build automated AI red teaming.

- High-context detection and response: You will build AI systems that can quickly triage and respond to threats, both from internal agents and external attackers.

- Blue-team engineering: Detection engineering, telemetry pipelines, incident response, and hardening across our cloud infrastructure, endpoints, and identity systems.

- Securing a unique attack surface: METR's evaluation infrastructure runs frontier AI agents. In the past, we've run pre-deployment model evaluations - executing untrusted, model-generated code at scale on multi-day tasks.

- Enabling bleeding-edge research: You'll work closely with our researchers to make dangerous-capability experiments safe to run. We often face extreme reward hacking and evaluation awareness during our pre-deployment evaluations, and expect internal threats from agents to become more extreme.

## Why this role matters

- METR handles some of the most sensitive artifacts in AI - pre-release frontier model access, confidential lab information, and transcripts with raw chain-of-thought. Labs and policymakers trust us with this because of our security posture, and keeping that trust is necessary for everything else we do.

- As AI agents are used more aggressively by malicious actors for cyber offense operations, and METR's salience rises in the public eye, we expect to face increasingly sophisticated attacks. Strengthening security at METR can be one of the highest-leverage roles to ensure third parties continue to have access to confidential information necessary to inform the world about current risks.

- METR is one of the first organizations to see and closely study misalignment incidents that involve models breaking out of sandboxes, attacking our infrastructure, manipulating graders, and more. We also may pursue incident investigations embedded in frontier labs, in which case internal experience with similar failures will be critical.

Required skills

- Deep security expertise: You have strong fundamentals across systems, networks, cloud, and identity.
- Offensive security: You have experience acting like an attacker, whether through red teaming, penetration testing, or adversarial research.
- AI/LLM engineering: You build with AI: agent pipelines, LLM-powered tooling, automated workflows, and understand current limitations of those tools.
- AWS: You should know AWS very well, including a deep understanding of IAM policies.

We don't screen on certifications, degrees, or years of experience.

Nice to haves

- Detection engineering at scale: Experience with SIEM/detection pipelines, writing and tuning detections, and threat hunting.

- Cloud and container security: AWS (especially non-trivial IAM), Kubernetes, and infrastructure-as-code environments.

- Incident response: You've led or worked severe incidents, ideally those involving AI agents.

- AI security research: Familiarity with prompt injection, agent containment, model supply-chain risks, or red teaming AI systems themselves.

Ideally you have experience with a good portion of these technologies:

- AWS: cloud-native software platforms
- EKS
- Lambda
- ECS
- IAM (in-depth)
- SQS
- CloudWatch
- SecurityHub & GuardDuty
- PostgreSQL: RLS, serverless Aurora
- Pulumi: IaC
- DataDog: SIEM
- Okta: IdP
- Google Workspace: IdP
- Tailscale: networking
- CrowdStrike Falcon: endpoint security

Our Culture

METR is a mission-driven organization. We believe our work can meaningfully shape humanity's future for the better, and we want to be the best people in the world doing this work. We have a tight-knit, collaborative research culture rooted in truth-seeking and integrity. We're fiercely committed to producing high-quality, trustworthy science. We're honest and transparent about our results, especially when they may go against the grain. We've earned trust as reliable partners who handle confidential information with care. We maintain a low-ego, drama-free environment focused on what matters.

Hybrid Preferred: Our technical team members are in our office in Berkeley 3-5 days/week. We would ideally like for you to be in person too, but we are happy to be flexible here. If you lack US work authorization and would like to work in-person, we can likely sponsor a cap-exempt H-1B visa for this role.

We encourage you to apply even if your background may not seem like the perfect fit! We would rather review a larger pool of applications than risk missing out on a promising candidate for the position.

We are committed to diversity and equal opportunity in all aspects of our hiring process. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We welcome and encourage all qualified candidates to apply for our open positions.

## About METR

## Company Overview
- **One-liner**: METR (pronounced "meter") is a non-profit research organization that develops scientific methods to assess catastrophic risks from advanced AI systems by evaluating their autonomous capabilities.
- **Entity Type**: Non-profit (funded by donations, not a typical private company; no equity)
- **Headquarters**: Berkeley, California, USA
- **Founded**: Not explicitly stated, but founded by Beth Barnes; likely ~2021–2022
- **Founders**: Beth Barnes (Founder, CEO)

## Core Business
- **Primary industry**: AI safety research and evaluation
- **Target customers**: AI developers (e.g., OpenAI, Anthropic, Google DeepMind, Meta, Amazon), governments, and the broader public
- **Mission or purpose**: "Develop scientific methods to assess catastrophic risks stemming from AI systems’ autonomous capabilities and enable good decision-making about their development."

## Products & Services
- **Frontier AI Capability Evaluations**: Systematic assessments of how autonomously AI systems can perform tasks (e.g., conducting research, developing apps, cyberattacks, self‑hardening). Published as open research.
- **Risk Assessments & Safety Policies**: Advises AI developers and governments on risk assessment methodologies, including the "Responsible Scaling Policies" approach adopted by nine leading AI labs.
- **Time‑Horizon Research**: Open‑source analysis showing that the length of tasks AI agents can complete doubles every ~7 months, a key input for forecasting transformative AI timelines.
- **Evaluation Platform**: An open‑source platform built on Inspect AI for running AI agent evaluations at scale.
- **Monitorability Evaluations**: Research on detecting AI agents attempting to evade monitoring or perform side tasks, including datasets of "reward hacking" and "sandbagging" behaviors.
- **Productivity RCT**: A randomized controlled trial with experienced open‑source developers measuring how much AI tools actually boost productivity (finding systematic overestimation).

## Market Standing
- **Valuation/Market Cap**: Not applicable (non‑profit)
- **Key Metric**: Funding – METR is supported by donations from major foundations and individuals. Notable donors include The Audacious Project (TED), Jane Street, Sijbrandij Foundation, Pew Charitable Trusts, Schmidt Sciences, Packard Foundation, and others. Small part of income from a technical assistance contract with the European AI Office. **No funding from AI companies** (maintains independence).
- **Notable Investors/Partners**: Partners with OpenAI, Anthropic, Google DeepMind, Meta, Amazon (pilot risk assessments); member of NIST AI Safety Institute Consortium, California Cybersecurity Task Force, UK AI Security Institute; technical assistance to European AI Office.
- **Growth Signals**: Growing team (multiple open roles), expanding into cyberforensics and embedded assessments, research cited widely in AI safety policy, and adoption of their Responsible Scaling Policies by major developers.

## Competitive Advantages
- **Independence**: No funding from AI companies, enabling unbiased, transparent research.
- **Scientific Rigor**: Publishes all research openly; uses empirical methods (RCTs, time‑horizon analysis) rather than speculation.
- **Policy Influence**: Their frameworks (e.g., Responsible Scaling Policies) are now industry standards, and they advise governments globally.
- **Deep Technical Expertise**: Team of researchers and engineers building state‑of‑the‑art evaluations for autonomous capabilities, including security‑relevant evaluations.

## Strategic Focus
- **Current priorities**: Developing methodologies to track AI loss‑of‑control risk, improving monitorability evaluations, expanding cyberforensics capabilities, and scaling the team to meet growing demand for independent evaluations.
- **Direction for growth**: Increasing influence on AI governance, deepening partnerships with governments and companies, and building tools for continuous risk assessment.

## Why Work Here
- **Mission‑driven**: Direct contribution to aligning AI development with public safety, working on one of the most critical problems of our time.
- **Compensation**: Highly competitive with top AI labs (salary ranges $328K–$687K for technical staff, $150–$300/hr for contractors), plus benefits like medical/dental/vision, wellness ($1,500/yr), mental health ($6,000/yr), professional development ($5,250/yr), unlimited PTO.
- **Work environment**: Small, fast‑moving, mission‑driven team based in Berkeley. On‑site preferred for technical roles (at least a few days a week), but hybrid and remote (including international) can be accommodated. Operations roles require in‑person.
- **Hiring process**: Unique focus on work tests (1–3 take‑home tasks) and a 1–2 day paid work trial (travel and lodging reimbursed). Interviews are given substantially less weight. Commitment to diversity and equal opportunity.
- **Culture**: Open, transparent, and empirical; values rigor and independence. Visa sponsorship available for technical roles.

## Sources
1. [metr.org](https://metr.org/)
2. [metr.org/about](https://metr.org/about#our-team)
3. [metr.org/careers](https://metr.org/careers)
4. [metr.org/hiring](https://metr.org/hiring)
5. [jobs.lever.co/metr](https://jobs.lever.co/metr)

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