We treat your time as the scarce asset that it is. Mash has an open and direct culture.

About Mash

We're a dynamic team with experience at startups, and scaling products at big tech including Google, Amazon, Ada, D2L, CourseHero, Rakuten, Dayforce, PagerDuty, ROSS Intelligence & Lazer. We have top AI staff, including from programs such as MScAC, and advisors that have built startups and led some of the largest organizations in big-tech over the past 15 years. Mash investors include Whitecap Venture Partners, Castle Island Ventures, Maple VC, Strategic Cyber Ventures, Aquanow, Spacecadet, and angel investors including Sunny Madra (formerly Groq, now NVIDIA), Balaji Srinivasan (former CTO of Coinbase, author of The Network State), Austin Hill (co-founder of Zero-Knowledge Systems and Blockstream), Josh Troy (multi-startup CFO/co-founder, including Urbint) and John Pfeffer (former partner at KKR, co-founder of Pfeffer Capital).

As an AI-focused software engineer on the Mash team, you will: Ship core AI features within the Mash platform. Apply information retrieval techniques for search and retrieval-augmented generation (RAG), working with embedding models and vector databases. Develop processes and tooling for measuring and iterating on LLM output quality, leveraging eval frameworks and observability platforms.

Develop bespoke ML/NLP models, when appropriate. Build production data pipelines to ingest knowledge sources.



Stay up to date on cutting-edge research in the ML/NLP space and identify opportunities to apply new techniques within the Mash platform.

AI: Always iterating and changing - recently - Python, Agent Harnesses (e.g., Python (FastAPI, Pydantic, SQLAlchemy), TypeScript, React Native with Expo, Next.js.

Data: Postgres, Cloud Storage, Prefect.

Cloud

Run, Cloud SQL, Pub/Sub, Eventarc), Terraform, Docker, Dagger, Kubernetes, Tilt, OpenTelemetry. 4+ years of building production software at scale with a multi-year focus on AI. ~ Proficiency in 1+ programming languages, such as Python, Go, Rust, C++, or Java. ~ You've shipped LLM-powered features to real users: agents and tool calling, context design, retrieval and structured outputs. ~ You've built evals, datasets or regression checks that drive meaningful and provable improvement in a customer/user experience. ~ Experience with event-driven systems, building cloud-native software (with cloud providers such as Google Cloud Platform, Amazon Web Services, Microsoft Azure, etc.), working with data (both structured and unstructured) and developing data pipelines. ~ You use AI coding agents as a normal part of how you build. ~ Bonus: agent harnesses, structured interactions, speech or audio pipelines, entity resolution, sandboxing and isolation, privacy-preserving ML. Has robust user empathy, and a user experience first mindset. #

📌 AI Software Engineer Intern (Toronto)
🏢 Mash
📍 Toronto