Senior Manager - Recommendations

SoundCloud Ltd
London
11 months ago
Applications closed

Related Jobs

View all jobs

AI & Data Science Manager / Senior Manager

AI & Data Science Manager / Senior Manager

AI & Data Science Manager / Senior Manager

Databricks Data Engineer -London | Up to £100K

Senior AI & Data Science Leader

Data Engineer (SC Cleared)

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.

SoundCloud is the #1 destination to discover what's next in music. And that means, our Music Recommendation is at the core of SoundCloud’s strategy . As the Senior Manager of the Recommendation teams, you will drive technical strategy and execution of projects to help music fans find great music and help creators to find the best possible audience for their music. You will work closely with Product Managers and UX Researchers to develop experiences helping our customers to find great music in our ever-growing catalog of ~300 million tracks. You will manage the Recommendation teams that research, design, develop and maintain recommendation services at SoundCloud. You will be responsible for products such as personalized home feed ranking, personalized playlists generation, related music recommendations and artist stations as well as ideation and delivery of new services and capabilities.

In your role you will have end-to-end ownership of the software engineering and machine learning infrastructure necessary to leverage the data and other resources in order to build and deliver search and recommendation mechanisms. You will prioritize activities, delegate and supervise all engineers’ activities and deliverables. As a people manager you will be responsible for hiring, managing and developing a group of talented software engineers working with cutting-edge technologies such as microservices, Scala, TypeScript/React, Python, data processing platforms such as BigQuery and other Cloud Platform services.You will also grow and work with the team of machine learning engineers and scientists working with variety of ML frameworks including (but not limited to) PyTorch and Tensorflow. We care much more about your general engineering and ML skills and positive attitude towards getting things done than any prior knowledge of a particular language or framework.

About the team: We’re a team of 15 people from over 10 countries. We are passionate about what we do, the problems we’re solving for creators and fans, and of course, music. We value trust between team members, experimentation, accountability, and work/life balance. We are an agile, hard-working team who delivers simply and quickly, while having fun in the process!

Key responsibilities:

Work closely with the Product Managers, UX Researchers and Designers to transform Discovery at SoundCloud. Broadcast the Discovery vision to inspire technical and non-technical stakeholders. Drive short and long-term objectives and key results with full responsibility for executing the OKRs. Be a pragmatic voice showing where to invest engineering effort to drive business outcomes. Lead, support and mentor Engineers and Scientists. Recruit and retain top-notch talents for your teams. Act as a technical liaison and representative for other teams, groups, and the company. Keep in touch with industry trends and technological advances and highlight opportunities that apply to SoundCloud.

Required skills and experience:

Experience with managing engineers and scientists. A strong engineering and data science background, knowledge and experience on recommendation engine and machine learning systems, being able to evaluate complex technical decisions. Industry experience building data-driven products and implementing machine-learning solutions at scale. Experience in maintaining large cloud systems over time, establishing a technical roadmap and balancing product and engineering concerns Extensive experience with and in-depth knowledge of agile methodologies. Demonstrated expertise in problem solving and technical innovation. Recruiting and culturally-informed communication skills.

If you are excited by the opportunity to directly impact the daily experience and happiness of millions of people around the world, giving them the power to share and connect through music, we’d love to hear from you. 

Read about engineering at SoundCloud.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.