About the role

We're looking for someone to own the build and own the evidence.

We're building a training app that makes the gear people already own more useful. Our founder built the working version, and it's in private TestFlight testing now. Alongside it we're running a wearable research program testing whether affordable sensors can give people better coaching.

You’ll be the technical owner of both. You'll take a real app to public launch and keep it running, and you'll design the sensor and ML experiments that tell us what actually works. You work directly with the founder. This is hand-on: you write the code, look at the data and make the calls.

The roadmap: public app launch in December 2026 , and sensor launch by March 31, 2027.

What's in it for you

This is a 6-month contract role ending in March 2027, with the potential to transition to full-time based on performance and business needs

CAD $80,000-$100,000 base salary

Health Spending Account

A Calgary office you'll actually want to come into

Employee discounts on all our gear

Access to our staff gym

A team that actually likes what they do

The schedule & location

This is a hybrid role based at our Calgary location, where the core hours are Monday to Friday from 8:00am to 4:30pm

The non-negotiables
You build with Claude Code first, and you check its work after. You can let Claude take the lead and you act as an architect.

You lift. You know sets, reps, RPE, progression and rest periods, and you're at home around barbells, racks, benches, dumbbells and cable machines. No coaching certifications needed. You do need to understand what our customers are doing in their garage.

You're in Calgary.



You live here or you'll move here before your start date. The job is hybrid but you are expected to come on-site around 3 times a week to work with our equipment, coaches and product team, so remote from another city or country won't work.

What you'll do

Take our React Native/Expo and TypeScript app, Supabase/Postgres backend and local-first data through release, monitoring and day-to-day operation

Build the hard backend and data pieces yourself: reliable sync, access control, sensor ingestion, versioned datasets, model interfaces, and failures we can actually see

Work with our team of 2 in-house personal trainers, 2 biomechanical engineers and the visionary to design the wearable measurement and ML experiments: reference comparisons, simple baselines, participants and sessions kept separate, uncertainty estimates and honest limits on what we release

Turn validated findings into coaching features with confidence checks, a manual fallback, and sensible behaviour when the signal is missing or unreliable

Set technical priorities with the visionary, review AI-assisted code and analysis, and keep decisions and experiment records reproducible

What Success Looks Like

Within 90 days you own the release process of the app

The first wearable experiments are running, with reproducible baselines





The app is on track for its December public launch on Android, iOS and web

When we make the March wearables call, it rests on evidence, not a demo

What We're Looking For

You've shipped production mobile apps and supported them after launch

You've personally built and properly evaluated an applied ML system, and that evaluation drove a real product or deployment decision

Solid backend, SQL, API and authorization skills, plus practical React/TypeScript. You can own mobile releases and debug state, sync and recovery problems

Python, statistics and applied ML fundamentals. You can explain leakage, reference error, calibration, and why a model that looks great in a notebook falls apart on new users

You've owned technical design and made delivery calls on your own. That's usually 6+ years, but depth matters more than the number

You improve an existing codebase instead of rewriting it, ship small releases you can verify, and explain trade‑offs in plain language

Experience with iOS and Android development

Experience with BLE data capture

Bonus Points

React Native/Expo and Supabase

Wearable or time‑series data, signal processing

Model deployment

You own the app, the data pipeline and the ML calls. We care more about what you've built than where you learned it.

The Interview Process

30 minute screening with our HR Coordinator

60 minute screening with our hiring team

Paid, time‑bound technical assessment

60 minute follow up to discuss technical assessment

60 minute technical follow-up to discuss assessment

Reference check (include in resume)

Decision made and offer sent out

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📌 Senior Technical Lead (Full-Stack & Applied ML) (Alberta)
🏢 Stichting Mission on Wheels
📍 Alberta