Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer II, Messaging Optimization

Spotify AB
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer II - Decision Analytics in London - American Express Global Business Travel (GBT)

Data Engineer II - QuantumBlack, AI by McKinsey

Data Engineer II - Databricks and Python

Data Engineer II - Databricks and Python

Data Engineer II – QuantumBlack, AI by McKinsey

Data Engineer II

We're looking for a Machine Learning Engineer II to join our team focusing on messaging optimization. Through our messaging platform, we communicate with users to connect them with valuable audio content and to help the business grow.

Submit your CV and any additional required information after you have read this description by clicking on the application button.Location:LondonJob type:PermanentThe team's vision is to build the machine learning models and infrastructure that offers a fully personalized and ML-optimized experience for listeners throughout their user journey that powers every messaging and conversion campaign at Spotify.Our team is a combination of Machine Learning Engineers, Data Engineers, Backend Engineers, and Data Scientists.What You'll Do:Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development.Collaborate with a multi-functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways.Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users.Help drive optimisation, testing, and tooling to improve quality.Be part of an active group of machine learning practitioners in your mission and across Spotify.Who You Are:You have a strong background in machine learning, theory, and practice.You are comfortable explaining the intuition and assumptions behind ML concepts; experience in the messaging space is a plus.You have hands-on experience implementing and maintaining production ML systems in Python, Scala, and using libraries like TensorFlow or PyTorch.You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models.You preferably have experience with cloud platforms like GCP or AWS.Where You'll Be:For this role, you will be based in London.

#J-18808-Ljbffr

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.

Jobs

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.