At a Glance
- Tasks: Build innovative ML features for the world's leading running app.
- Company: Join Runna, a fast-growing tech company revolutionising fitness training.
- Benefits: Flexible working, competitive salary, 25 days holiday, and private health insurance.
- Other info: Collaborative culture with excellent career growth and mentorship opportunities.
- Why this job: Shape the future of fitness with cutting-edge technology and a passionate team.
- Qualifications: 3+ years in ML engineering, strong Python skills, and AWS experience.
The predicted salary is between 60000 - 80000 € per year.
Runna helps 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.
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.
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:
- 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.
Senior Software Engineer, Machine Learning in London - Runna employer: Runna
Runna is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about fitness technology. With flexible working arrangements, regular salary reviews, and generous benefits including private health insurance and enhanced family care policies, employees are supported both personally and professionally. The opportunity to collaborate closely with founders and a highly-skilled engineering team in the vibrant setting of London makes Runna an attractive place for talented individuals looking to make a meaningful impact in the world of running and fitness.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Software Engineer, Machine Learning in London - Runna
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Runna. A friendly chat can go a long way, and who knows, they might even put in a good word for you!
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to machine learning or fitness tech, make sure to highlight that. It’s a great way to demonstrate your expertise and passion.
✨Tip Number 3
Prepare for the interview by understanding Runna's mission and values. Think about how your experience aligns with their goals of helping runners. Tailor your answers to show you're not just a fit for the role, but for the company culture too!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Runna team!
We think you need these skills to ace Senior Software Engineer, Machine Learning in London - Runna
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Software Engineer, Machine Learning. Highlight your experience with AWS, Python, and any relevant ML projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for fitness tech and how you can contribute to our mission at Runna. Be sure to mention specific experiences that demonstrate your ability to build and deploy data-driven models.
Showcase Your Projects:If you've got any personal or open-source projects related to machine learning or fitness apps, don’t hesitate to include them! We love seeing practical applications of your skills, so share links or descriptions of your work.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Runna!
How to prepare for a job interview at Runna
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and AWS experience. Be ready to discuss specific projects where you've deployed models and built MLOps pipelines. This will show that you not only understand the theory but have practical experience too.
✨Show Your Passion for Fitness Tech
Since Runna is all about helping runners, it’s a great idea to express your enthusiasm for health and fitness technologies. Share any personal experiences or projects related to fitness apps or training plans to connect with the team’s mission.
✨Prepare for Collaboration Questions
Expect questions about teamwork and collaboration, especially since you'll be working closely with coaches and other engineers. Think of examples where you've successfully collaborated in cross-functional teams and how you’ve contributed to shared goals.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company’s future. Inquire about their vision for the next generation of the training engine or how they plan to leverage new ML technologies. This shows you're thinking ahead and are genuinely interested in being part of their journey.