(Senior) Software Engineer, Machine Learning

We're putting together a talented team to build the #1 training platform for Runners

We help everyday runners become outstanding by providing world-class training, coaching and community for everyone, whether you're improving your 5k time or training for your first marathon. To date we have built iOS, Android and Apple watch apps that help people achieve their goals by coaching them through the full journey and syncing to their favourite fitness devices.

We’re growing extremely fast and in November 2023 closed a new £5M funding round led by JamJar with participation from Eka Ventures, Venrex and Creator Ventures. We want to grow as fast as we can into the future and are looking for individuals who will help us get there. For more about our background and growth check out our Careers Page!

We’re now looking ahead to the future and the people that want to help us build and scale Runna. Our aim is to reach millions of subscribers in the next 5 years and be the go-to training platform for any runner. Now is a magical time to join, we're still small, and everyone makes a foundational difference.

Who we’re looking for

We are looking for talented, creative and positive team players to join our highly-skilled Cross-Functional Engineering Team to help build the next generation of training engine that powers what we do. As part of this work, you’ll be working closely with the engineering, product and coaching team to build an engine that will dynamically build users the optimal training plan, whilst adapting based on external inputs (from previous workouts to live recovery tracking). You will work closely with our founders and CTO to help shape the future of Runna who will be there to support you all the way along this exciting journey.

Working with state of the art ML technologies, you’ll help build the #1 running app in the world, pioneering the way that people train and use fitness apps

As a Machine Learning Engineer your role will include:

• Architect, build, test and deliver new and improved running engine features to generate personalised, adaptive training plans for tens of thousands of active users
• Creating SOTA models/algorithms and deploying them in a scalable, maintainable manner, and building MLOps pipelines to support this
• Building data pipelines in AWS, to support creation of models and analytics
• Mentoring others in the team on best practice in these areas
• Collaborate with coaches to best deliver their expertise to users

Our tech stack

Below you can find a small reflection of our current tech stack:

Frontend:

• React Native (iOS and Android)
• Typescript
• GraphQL (Apollo Client)
• Fastlane
• SwiftUI (Apple Watch)
• Maestro E2E tests

Backend:

• Serverless (AWS)
• Lambdas (NodeJS & Python)
• AWS AppSync
• DynamoDB, S3, SQS, SNS, Sagemaker
• Postman API tests

All the other good stuff:

• Sentry
• GitHub Actions
• Intercom, Mixpanel
• RevenueCat
• App Store Connect / Play Store
• Figma

Python / Machine Learning Engineer Interview process

Our aim is to keep the interview process as straightforward and enjoyable as possible, and will consist of the following stages:

1. Kick off! (apply here)
2. Introductory chat (30 minutes video call)
3. Take home technical task (max 1-2 hours to complete)
4. 1.5 hour technical interview (the first half of the call will be used to discuss the take-home technical task from the previous stage and the second half will be some general architecture/tech questions)
5. Meet the team and in-person chat (in-person chat with founder(s), rest of the team and technical discussion)

Once the process is finished, we promise to let you know our decision as soon as possible.

Requirements

What experience we’re looking for

If you don’t quite meet all of the below skills, we’d still love to hear from you as we might be able to tweak the role slightly or offer you a position better suited for you. You can apply directly below or contact us if you’re still unsure.

Your key experience:

• 3+ years in an ML engineer/MLOps role or similar
• 2+ years working with AWS
• You’ve deployed models to production, monitored and iteratively improved them in a cloud environment
• You’ve trained models (bonus for deep learning) using large volumes of data
• An analytical degree (e.g. Computer Science, Maths, Physics, Engineering)

Your key skills:

• Building and deploying data driven models in AWS
• Strong Python programming
• Confident creating scalable and maintainable:
• MLOps pipelines
• Data processing pipelines and storage in AWS
• Understanding of LLMs and how to best interact with them
• Deeply analytical and rigorous with a commitment to producing high-quality output
• A pragmatic mindset, with strong communication and collaboration skills
• Confidence in working with a highly-skilled engineering team in a fast-paced, iterative environment
• Confident delivering features end-to-end, from architecture design and building through to releasing, testing and supporting
• Enthusiasm for our ways of working which include:
• Iterative development, continuous deployment and test automation
• Knowledge sharing, pair programming, collaborative design & development
• Shared code ownership & cross-functional teams

Bonus points if you:

• Have experience with vector DBs
• Are experienced in deployment, release cycles or CI/CD
• Have experience monitoring models and algorithms in production
• Have experience with Serverless architectures
• Have experience with AWS
• Have open-source contributions
• Are experienced delivering features full-stack
• Have a strong interest in the health/fitness technologies

Benefits

Benefits and options

We offer a salary of £57.5k - £100k+ (depending on experience), plus equity in the form of Runna stock options.

** Based on years of direct, relevant experience. Software Engineer III £57.5-67.5k, Software Engineer IV £70-85k, Software Engineer V £90k+

We'll be growing our package of benefits over time. We currently offer:

• Flexible working (we typically work 2-3 days in our office in Vauxhall)
• Salary reviews every 6 months or whenever we raise more investment
• 25 days of holiday plus bank holidays
• A workplace pension scheme
• A brand new Macbook, a running watch of your choice, and anything else you need to do your best work
• Private health insurance
• Enhanced family care policy (3 months fully paid leave when a new Runna joins the family, fertility support & other benefits)
• An hour slot each week (during work time) to do a Runna workout