National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Machine Learning Engineer

SoundCloud Ltd
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer - up to £135k base plus equity

Senior Machine Learning Engineer - up to £135k base plus equity

Senior Machine Learning Engineer - up to £135k base plus equity

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 aSenior Machine Learning Engineerto join ourAds team. As part of the Revenue Group, our mission is to provide anyone on any budget access to the music and communities they love through tailored and sustainable monetization and user engagement.


The Ads team at SoundCloud operates as a cross-domain unit that collaborates closely with various departments to optimize the advertising experience for listeners while maximising revenue potential. By carefully balancing user engagement with strategic ad placement, the team works tirelessly to build a sustainable platform that provides consistent and meaningful revenue streams for artists across the platform.


Key Responsibilities:


As a Senior Machine Learning Engineer, you will work closely with Scientists to move ML projects from ideation to production. This includes designing, building, evaluating, and deploying scalable models that directly impact the experience of millions of users globally. 


You’ll lead the end-to-end development process, from architecture design to model deployment and monitoring. Beyond technical implementation, you’ll set engineering standards, mentor teammates, and influence strategic decisions. You’ll champion best practices for testing, reliability, and long-term maintainability of ML systems and infrastructure, raising the engineering bar across SoundCloud.


We value your technical leadership, engineering craftsmanship, and passion for building high-quality ML products that drive meaningful and lasting impact.

Experience and Background:

Proven track record of successfully releasing large-scale ML models to production, including ownership of model design, training/ fine-tuning, evaluation, and optimization of both training and inference performance. Familiarity with state-of-the-art recommendation systems and large language models (LLMs) is a strong plus


Demonstrated experience building and scaling robust ML infrastructure and tooling, including components such as deployment automation, model lifecycle management, monitoring, containerization, and orchestration. Proficiency with cloud platforms (e.g., GCP, AWS, Azure) is expected
Strong background of professional software engineering practices, including version control, test-driven development, peer reviews, CI/CD, and clean code principles across the ML system lifecycle
Ability to clean, process, and analyze large datasets, as well as experience conducting and interpreting A/B tests using SQL
Ability to make informed build-or-buy decisions by evaluating technical trade-offs, integration complexity, long-term maintenance, and business impact
Expert-level coding skills in Python, Scala, Java, or similar languages, with deep hands-on experience in ML frameworks (e.g., TensorFlow, PyTorch) and distributed data systems (e.g., Spark, BigQuery)
Effective communicator and technical collaborator who proactively drives initiatives in cross-functional, agile teams. Comfortable mentoring peers, leading discussions around architecture and design, and delivering impactful, scalable solutions

Preferred Experience:

Demonstrated expertise in spearheading the end-to-end development of machine learning solutions specifically within the advertising industry, including system architecture design, implementation, and production deployment focusing on reliability and scalability


Experience in designing and deploying (including security, reliability and scale) of ML solutions on the cloud, such as AWS or GCP
Experience building solutions involving large datasets and/or ML models using distributed computing frameworks and technologies

National AI Awards 2025

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.

10 AI Recruitment Agencies in the UK You Should Know (2025 Job‑Seeker Guide)

Generative‑AI hype has translated into real hiring: Lightcast recorded +57 % year‑on‑year growth in UK adverts mentioning “machine learning”, “LLM” or “gen‑AI” during Q1 2025. Yet supply still lags. Roughly 18,000 core AI professionals work in the UK, but monthly live vacancies hover around 1,400–1,600. That mismatch makes specialist recruiters invaluable—opening stealth vacancies, advising on salary bands and fast‑tracking interview loops. But many tech agencies sprinkle “AI” on their website without an active desk. To save you time, we vetted 50 + consultancies and kept only those with: A registered UK head office (verified via Companies House). A named AI/Machine‑Learning or Data practice.

AI Jobs Skills Radar 2026: Emerging Frameworks, Languages & Tools to Learn Now

As the UK’s AI sector accelerates towards a £1 trillion tech economy, the job landscape is rapidly evolving. Whether you’re an aspiring AI engineer, a machine learning specialist, or a data-driven software developer, staying ahead of the curve means more than just brushing up on Python. You’ll need to master a new generation of frameworks, languages, and tools shaping the future of artificial intelligence. Welcome to the AI Jobs Skills Radar 2026—your definitive guide to the emerging AI tech stack that employers will be looking for in the next 12–24 months. Updated annually for accuracy and relevance, this guide breaks down the top tools, frameworks, platforms, and programming languages powering the UK’s most in-demand AI careers.

How to Find Hidden AI Jobs in the UK Using Professional Bodies like BCS, IET & the Turing Society

Stop Scrolling Job Boards and Start Tapping the Real AI Market Every week a new headline announces millions of pounds flowing into artificial-intelligence research, defence initiatives, or health-tech pilots. Read the news and you could be forgiven for thinking that AI vacancies must be everywhere—just grab your laptop, open LinkedIn, and pick a role. Yet anyone who has hunted seriously for an AI job in the United Kingdom knows the truth is messier. A large percentage of worthwhile AI positions—especially specialist or senior posts—never appear on public boards. They emerge inside university–industry consortia, defence labs, NHS data-science teams, climate-tech start-ups, and venture studios. Most are filled through referral or conversation long before a recruiter drafts a formal advert. If you wait for a vacancy link, you are already at the back of the queue. The surest way to beat that dynamic is to embed yourself in the professional bodies and grassroots communities where the work is conceived. The UK has a dense network of such organisations: the Chartered Institute for IT (BCS); the Institution of Engineering and Technology (IET) with its Artificial Intelligence Technical Network; the Alan Turing Institute and its student-driven Turing Society; the Royal Statistical Society (RSS); the Institution of Mechanical Engineers (IMechE) and its Mechatronics, Informatics & Control Group; public-funding engines like UK Research and Innovation (UKRI); and an ecosystem of Slack channels and Meetup groups that trade genuine, timely intel. This article is a practical, step-by-step guide to using those networks. You will learn: Why professional bodies matter more than algorithmic job boards Exactly which special-interest groups (SIGs) and technical networks to join How to turn CPD events into informal interviews How to monitor grant databases so you hear about posts months before they exist Concrete scripts, portfolio tactics, and outreach rhythms that convert visibility into offers Follow the playbook and you move from passive applicant to insider—the colleague who hears about a role before it is written down.