Machine Learning Engineer Language

New Yesterday

We in the Machine Learning product area in the Activation, Retention, Conversion studio are focused on building robust and scalable machine learning solutions that can personalize activation, retention and conversion funnels to improve important business metrics like SUBS and MAU. Through our messaging platform as well as other discovery & conversion surfaces, we communicate with users to connect them with valuable audio content and to help the business grow. We are looking for a passionate Junior Machine Learning Engineer to help us accomplish our mission: enable impactful ML optimisation opportunities in new domains (Awareness & Acquisition, Commerce & Customer Support, Free & Paid Products) and bootstrap the GenAI Strategy of the Subscriptions Mission.
Contribute to designing, building, evaluating, shipping, and refining Spotifys 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
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
You'll work on projects like; You have at least 2 years of experience in applied Machine Learning Engineering
You have a strong background in machine learning, theory, and practice
You are comfortable explaining the intuition and assumptions behind ML concepts
You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages
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
You care about agile software processes, data development, reliability, and focused experimentation
There will be some in person meetings, but still allows for flexibility to work from home. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - were here to support you in any way we can.
Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the worlds most popular audio streaming subscription service.
Extensive learning opportunities, through our dedicated team, GreenHouse.
Flexible share incentives letting you choose how you share in our success.
Global parental leave, six months off - for all new parents.
All The Feels, our employee assistance program and self-care hub.
Flexible public holidays, swap days off according to your values and beliefs.
Engineering Manager, Customer Service Platform
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Location:
London
Job Type:
FullTime