At a Glance
- Tasks: Build ML-powered features that enhance user engagement and satisfaction.
- Company: Join SoundCloud, the artist-first platform revolutionising music sharing.
- Benefits: Flexible work culture, generous PTO, and wellness benefits.
- Other info: Diverse and inclusive environment with excellent career growth opportunities.
- Why this job: Make a real impact on 200M+ users with your ML expertise.
- Qualifications: 1-2 years in ML systems and strong software engineering skills required.
The predicted salary is between 63000 - 77000 £ per year.
SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.
We are looking for a Senior Machine Learning Engineer to join our Recommendations Experience team, focusing on building ML-powered features that directly improve personalization, engagement, and satisfaction for our users. While this is an MLE role, you’ll bring strong engineering fundamentals and work across the full stack and end-to-end systems, from data pipelines to APIs to real-time serving, and everything in between. The Recommendations team ships ML-powered features that connect 200M+ users with music they'll love.
You will own features end-to-end: from understanding user needs with Product and Design, to architecting data pipelines processing billions of events, to building and shipping production ML systems that balance performance, cost, and user experience. This means working across BigQuery (trillion-row datasets), Airflow orchestration, real-time serving infrastructure (BigTable), APIs, and constant collaboration with Product, Design, Engineering, and Platform teams.
Key Responsibilities:- Develop, test, and productionize ML and LLM-based systems serving real users
- Design and build end-to-end ML pipelines, including data, features, training, and serving
- Make technical decisions considering cost, latency, complexity, and maintainability
- Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to build reliable, scalable solutions
- Set up monitoring, A/B testing, and metrics frameworks to measure real user impact
- Debug complex issues across data pipelines, ML models, and distributed systems
- Contribute to technical strategy and team best practices
- Leverage agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods
- 1-2+ years building ML systems in production - you understand the difference between a model that works in Jupyter and one that serves millions of users
- 4+ years of software engineering experience - you write production code, not just notebooks
- Strong Python and Scala (or Java/JVM) skills, with experience writing scalable, production code
- Experience building and deploying ML models end-to-end (data, training, serving, monitoring)
- Experience building and deploying LLM-based features in production
- Familiarity with integrating LLMs into ML systems (e.g. retrieval-augmented generation, model serving)
- Understanding of shared ML architecture across domains (e.g. search and recommendations)
- Strong focus on data quality and correctness, and how upstream data impacts downstream models and user experience
- Strong SQL skills for massive datasets (BigQuery, Spark)
- Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes)
- Experience with distributed data processing and ETL pipelines (Airflow, Spark)
- Familiarity with ML frameworks such as TensorFlow or PyTorch
About us: We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London). We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home. We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard. We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities.
Benefits:- Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
- Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
- Employee Equity Plan
- Generous professional development allowance
- Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
- We offer free German courses at beginning, intermediate and advanced
- Various snacks, goodies, and 2 free lunches weekly when at the office
Diversity, Equity and Inclusion at SoundCloud: SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status. At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.
Senior Machine Learning Engineer, Recommendations (Experience) in London employer: SoundCloud
At SoundCloud, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our Media Streaming Team offers unique opportunities for professional growth, allowing you to work with cutting-edge technologies in a dynamic environment that impacts millions of users globally. Join us in shaping the future of music delivery while enjoying a supportive atmosphere that values your contributions and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer, Recommendations (Experience) in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at SoundCloud or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to SoundCloud.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like SoundCloud.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like SoundCloud that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Machine Learning Engineer, Recommendations (Experience) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at SoundCloud.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at SoundCloud and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at SoundCloud
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If SoundCloud uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.