Member of Technical Staff, Intern
- Toronto, ON
- Hybrid
- Posted Aug 14, 2026
- 1 position
Opens an external site
- Employment type
- Internship / apprenticeship
- Experience level
- Entry, Junior · 0+ years
- Posting language
- English
- Working hours
- 40 hours per week
Job summary
You will manage the SRE Skills Bench open-source project by designing evaluation scenarios and expanding datasets for AI reliability testing. Additionally, you will collaborate with researchers and engineers to analyze results and promote the benchmark within the AI and reliability communities.
Job details
ABOUT ROOTLY At Rootly [https://rootly.com/], we are on a mission to be the go-to way companies respond when things go wrong, helping every organization be more reliable. We do this by building an industry-leading incident management platform that allows companies around the world consistently and quickly resolve incidents. We are not simply transforming an industry, we are carving an entirely new +$B segment ourselves and need incredible talent to achieve this ambitious goal together. Customers love Rootly. Some of the fastest growing companies around the world such as NVIDIA, Figma, Canva, Tripadvisor, Squarespace and more rely on Rootly to power their critical incident management process. They obsess over our delightful enterprise-ready platform and unique partnership model. See why our customers have reviewed us 5 stars on G2 [https://www.g2.com/products/rootly-manage-incidents-on-slack/reviews]. Investors love Rootly. We are backed by some of the most respected funds in the world from Y Combinator to operators like the CTO of Dropbox and GitHub. We'd be happy to disclose our entire funding and profitability picture live during the interview. As a culture we relentlessly put transparency first. We conduct monthly financial reviews as a team so everyone has a pulse on the health of the business and publish what we are building in our weekly changelog [https://rootly.com/changelog]. ABOUT ROOTLY AI LABS Rootly AI Labs is a fellow-led research and open-source team exploring how AI can make complex systems more reliable and the people operating them more effective. We build benchmarks, prototypes, and practical tools that test frontier models against real reliability challenges, from incident response and on-call health to agent behaviour under pressure. We work in public, move quickly from ideas to experiments, and share what we learn with the broader engineering community. Our goal is to turn promising AI research into useful, trustworthy systems while keeping human judgment at the centre. Work from Rootly AI Labs has been presented at NeurIPS, ACL, ICML, and Meta's AI Ops Conference. The Labs brings together researchers, operators, and builders from across the industry, with support from AWS, Google DeepMind, Anthropic, and Zalando. ABOUT THE ROLE You will manage SRE Skills Bench, Rootly AI Labs' open-source benchmark for measuring how well AI models handle real-world reliability engineering tasks. You will help move the project from research questions to public releases. This includes designing realistic SRE scenarios, expanding the evaluation dataset, running model evaluations, improving the benchmark infrastructure, and sharing the findings with the AI and reliability communities. The role combines applied AI research, technical project management, community building, and public communication. You will report directly to the Head of Rootly AI Labs and work closely with fellows, researchers, and engineers across the community. WHAT YOU'LL DO * Participate in shaping the roadmap and research questions for SRE Skills Bench. * Help build an active community around the benchmark and encourage outside contributions. * Create realistic evaluation tasks based on incident response, infrastructure, debugging, observability, and production operations. * Help develop reliable and reproducible methods for evaluating frontier and open-source models. * Analyze results and turn them into reports, technical articles, and public datasets. * Collaborate with SREs, researchers, model providers, and open-source contributors. * Evaluate how new models, agents, and coding environments perform on operational work. * Help establish SRE Skills Bench as the industry standard for evaluating AI on reliability engineering. WHAT YOU'LL NEED * Hands-on experience or a strong interest in SRE, infrastructure, platform engineering, DevOps, or production operations. * Familiarity with LLM evaluations, benchmarks, agents, or applied AI research. * An experimental mindset, with an interest in designing reproducible tests, examining imperfect results, and learning quickly. * A self-driven approach, with the initiative to make sound decisions and move ambitious projects forward with minimal guidance. * The ability to explain technical work clearly and enthusiasm for sharing it through articles, social media, and talks at meetups or conferences. * Comfort working in a hybrid environment and collaborating asynchronously with a curious, distributed team. ROLE DETAILS: Employment Type: Full-Time Intern Duration: Ongoing Internship with the possibility to conversion to a full-time role based on fit and project needs. You do not need to match every qualification. We value practical experience, sound judgment, curiosity, and the ability to turn ambitious ideas into useful work. Rootly is an equal opportunity employer. We aim to create an environment where every team member at Rootly feels like they belong so they can have a greater impact on our business and customers. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
What you’ll do
You will manage the SRE Skills Bench open-source project by designing evaluation scenarios and expanding datasets for AI reliability testing. Additionally, you will collaborate with researchers and engineers to analyze results and promote the benchmark within the AI and reliability communities.
Requirements
Candidates should have hands-on experience or strong interest in SRE, infrastructure, or DevOps, along with familiarity with LLM evaluations and AI research. You must possess an experimental mindset, strong self-driven initiative, and the ability to communicate technical findings clearly to a broader audience.
Listed skills
- Évaluation · Preferred
- Production · Preferred
- Incident Management · Preferred
- Technical · Preferred
- Reliability · Preferred
- staff · Preferred
- Health · Preferred
- Canva · Preferred
- management · Preferred
- Amazon Web Services · Preferred
- Time · Preferred
- Reliable · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- SRE
- Infrastructure
- Platform engineering
- DevOps
- Production operations
- LLM evaluations
- Benchmarks
- AI agents
- Applied AI research
- Technical project management
- Community building
- Public communication
- Incident response
- Debugging
- Observability
- Canva (Software)
- Figma (Design Software)
- AIOps (Artificial Intelligence For IT Operations)
- AI Research
- Curiosity
- Slack (Software)
- Research
- Artificial Intelligence
- Amazon Web Services
- Communication
- Incident Response
- Virtual Teams
- Github
- Incident Management
- Project Management
- Open Source Technology
- Operations
- Product Family Engineering
- Reliability Engineering
- Social Media
- Squarespace
- Reliability
- Trustworthiness
- Enthusiasm
Job areas
- Software
- Technology
- Science & Research
- Engineering
- Data & Analytics
- Member of Technical Staff
- Artificial Intelligence Engineer (General)
- Software Developers
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