Member of Technical Staff (Applied AI Engineer) job opportunity at MLabs.

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Date2026-03-10T12:55:33.830Z bot
MLabs Member of Technical Staff (Applied AI Engineer)
Experience: 4-years
Pattern: full-time
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loacation Toronto, Canada
loacation Toronto....Canada

Member of Technical Staff (Applied AI Engineer) Location:  Toronto (Office) On-site | Full-time Compensation: $140K - $260K Our client is seeking an Applied AI Engineer to join a high-growth, talent-dense team building open-source browser infrastructure for AI agents and applications. The organization provides a foundational Sessions API that enables developers to ship AI products capable of seamless web interaction. After experiencing 50x growth in 2025 driven by a vibrant open-source community and word-of-mouth adoption, our client is expanding their founding engineering team. This role sits at the critical intersection of product engineering, applied research, and community engagement. The successful candidate will not only ship production-grade code but will also conduct experiments to determine the most effective strategies for browser automation, subsequently translating those insights into frameworks and content that empower the global developer ecosystem. This is an intensive, high-impact role suited for engineers who thrive in fast-paced environments and are comfortable owning projects from conception to deployment. Key Responsibilities Framework Development: Build and maintain high-performance browser agent frameworks (e.g., in TypeScript) that vertically integrate LLMs with core browser infrastructure. Applied Research: Conduct rigorous experiments to evaluate model performance (GPT-4, Claude, Gemini, etc.), prompting strategies, and architectures specifically for browser automation. Ecosystem Integration: Develop and maintain integrations with major AI frameworks such as LangChain, CrewAI, and emerging agent platforms. Technical Evangelism: Author technical blog posts, documentation, and open-source demos that establish the organization as a primary authority on browser-based AI agents. Product Iteration: Work closely with the founding team and customers to translate real-world feedback into platform features and improvements. End-to-End Ownership: Scope, build, and ship "0 to 1" projects with minimal guidance, maintaining a focus on speed and pragmatism. Interview Process Initial Screening: A 30-minute introductory call with a Co-Founder. Take-Home Assessment: A practical test designed to evaluate technical problem-solving. Technical Leadership Interview: A focused discussion with the CEO. Coding Assessment: A technical interview and coding session with a Founding Engineer. Final Evaluation: A work trial or final interview (subject to candidate availability). Professional Experience: 4+ years of engineering experience with a proven track record of shipping production AI agents (e.g., research automation, web scraping, or form-filling tools). Technical Proficiency: Strong command of TypeScript/JavaScript and Python , with a deep understanding of both web development patterns and AI application architectures. AI Literacy: Deep familiarity with modern LLMs and the ability to quickly evaluate technical tradeoffs between different models and frameworks. Open-Source Mindset: Experience contributing to or maintaining open-source projects; comfortable building and engaging with a technical community. Communication Skills: Ability to create compelling technical content, including blog posts and developer-centric demonstrations. Operational Intensity: A high-intensity work ethic suited for a startup environment; ability to manage complex tasks with high autonomy. Preferred Qualifications: Experience as a founder, previous roles at AI-first companies, or a history of building developer tools that achieved significant community adoption. Technical Stack Overview: Frontend: React, TailwindCSS, Shadcn, Vite Backend: Fastify, Node.js, Zod, NATs, Drizzle Data/Infra: Redis, PostgreSQL, S3, Pulumi, Go, Firecracker VMs, Docker

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