Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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Product Engineer
- Location
- Toronto
- Type
- Full time
- Posted
- 13D AGO
About the role
All open roles
Careers
Product Engineer- Full time
- Hybrid, three days a week in the office
- Eastroom on Claremont St, Toronto
The role
Mash is the AI assistant for the people in your life, your to-dos, and everything you want to remember. As a Product Engineer, you will own user-facing product features end to end. You will get close to our users to understand what they need, help decide what to build with product and design, and ship it across the whole stack, including the Mash iOS app, our backend, and our AI systems.
Shipping will be only part of the job. You will stay with each feature after it launches, learn whether it made a real difference for the people using it, and help shape what comes next.
You keep a close pulse on what could be better, and you feel it when something gets in a user’s way. You also can’t stop imagining what Mash could become next: not a better version of a feature, but a whole new way to use it.
Here, you will have the room to act on those ideas: a small team, real users, and a product that is still taking shape. If you want to spend your days building the right things for our users and the business, we would love to meet you.
Culture
We treat your time as the scarce asset that it is. We respect people being heads-down and having the time to get into a flow. Distractions and context switching are things we work to minimize. We have meetings for specific purposes, and leverage async channels when appropriate.
Mash has an open and direct culture. We believe that not making a decision is a decision — and a terrible one at that. We have strong conviction and a bias for action. We can agree to disagree, and move forward after reviewing the details. As we learn, we will reevaluate, iterate and push forward.
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.
We don’t use any seniority titles, and plan not to for as long as feasibly possible (learn more about why).
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).
What you’ll do
- Talk to Mash users every week, through interviews, support conversations and App Store reviews, and turn what you hear into the next thing worth building.
- Write a short spec before you build: the problem, who it is for, what success looks like, and what we are leaving out.
- Own features from idea to the App Store and beyond, across the iOS app, our APIs, and the AI systems behind the assistant.
- Make product and UX decisions yourself, with product and design as partners, not gatekeepers.
- Ship small and often. Put rough versions in front of real users early, then iterate.
- Instrument what you ship, read the analytics (activation, retention, feature adoption), and decide whether to double down, change course, or remove it.
- Keep what you ship healthy in production: quality, performance, reliability, and the infrastructure and CI/CD behind it.
Our stack
- AI: We keep up with the state of the art and use whatever works best. Lately that means a bespoke agent harness, frontier and open-weight LLMs, decision models, speech-to-text and vision models, traditional NLP models, retrieval systems (graph, vector and keyword), and lots more.
- Application: Python (FastAPI, Pydantic, SQLAlchemy), TypeScript, React Native with Expo, Next.js.
- Data: Postgres, Cloud Storage, Prefect.
- Infrastructure: GCP (Cloud Run, Cloud SQL, Pub/Sub, Eventarc), Terraform, Docker, Dagger, Kubernetes, Tilt, OpenTelemetry.
You may be a fit if
- You are obsessed with how the product feels to use, down to the smallest details.
- You have 4+ years of building and shipping software, ideally consumer or prosumer products that real people use every day.
- You work across the full stack: TypeScript and React (React Native is a plus) on the front end, and a backend language such as Python, Go, Java, or C#.
- You have experience with relational databases (such as Postgres or MySQL) and cloud providers (such as Google Cloud Platform or AWS).
- You have owned a feature or product area end to end, and you can tell us what it did for users and for the business.
- You communicate clearly, in writing and in person, so a busy teammate gets it the first time.
- You use AI coding tools every day, and you know where they help and where they do not.
- Bonus: you have shipped LLM features, published an iOS app, run product experiments, or built a side project that people actually use.
Cultural fit
We’re looking for an individual who:
- Thinks in outcomes: starts from the user’s problem and the business result, and is happy to cut scope, or their own feature, to get there.
- Responds well to open-ended problems and thrives on autonomy — is a self-starter and problem solver.
- Thrives in team environments — is focused on team goals.
- Has great communication skills.
- Has a passion for lifelong learning.
- Has strong user empathy, and a user experience first mindset.
How to apply
Please reach out to us at careers@mash.com — and include a bit about yourself, your resume, three bullet points about why you are specifically interested in the position, and one feature you owned end to end: the problem, what you shipped, and what changed for users.
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