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For Companies At a Glance
- Tasks: Join us to design and develop machine learning solutions that enhance user experiences.
- Company: Spotify is a leading audio streaming platform focused on personalising user journeys.
- Benefits: Enjoy flexible work arrangements and a vibrant, inclusive workplace culture.
- Why this job: Make a real impact by optimising user engagement and driving business growth.
- Qualifications: 2+ years in Machine Learning Engineering with strong Python or Scala skills required.
- Other info: Work in London or Stockholm with a dynamic, agile team of experts.
The predicted salary is between 28800 - 48000 £ per year.
We in the Machine Learning product area within the Activation, Retention, Conversion studio focus on building robust and scalable machine learning solutions. Our goal is to personalize activation, retention, and conversion funnels to improve key business metrics like SUBS and MAU. We communicate with users through our messaging platform and other discovery & conversion surfaces to connect them with valuable audio content and support business growth.
We are seeking a passionate Junior Machine Learning Engineer to help us:
- Enable impactful ML optimization opportunities across new domains such as Awareness & Acquisition, Commerce & Customer Support, and Free & Paid Products.
- Bootstrap the GenAI Strategy for the Subscriptions Mission.
What You\’ll Do
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product through hands-on ML development.
- Collaborate with a multi-disciplinary agile team including user research, design, data science, product management, and engineering to develop new features that connect artists and fans in personalized ways.
- Prototype new approaches and scale solutions for our hundreds of millions of active users.
- Drive optimization, testing, and tooling to enhance quality.
- Join an active community of machine learning practitioners within your mission and across Spotify.
- Work on projects like optimizing ad load time, reducing features usage friction for free users to balance retention and conversion, and developing GenAI prototypes with partner squads.
Who You Are
- You have at least 2 years of experience in applied Machine Learning Engineering.
- You possess a strong background in machine learning theory and practice.
- You can explain the intuition and assumptions behind ML concepts clearly.
- You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages.
- Experience with Pytorch and TensorFlow is a plus.
- You are experienced in building data pipelines and self-sufficient in data acquisition for model development and evaluation.
- Experience with cloud platforms like GCP or AWS is preferred.
- You value agile software processes, data development, reliability, and focused experimentation.
- You are motivated to drive business impact.
Where You\’ll Be
- This role is based in London, UK or Stockholm, Sweden.
- We offer flexible work arrangements, with some in-person meetings required, typically three days per week.
Spotify is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We encourage applicants from all backgrounds to apply and offer accommodations during the recruitment process upon request.
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Junior Machine Learning Engineer - User Journey employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Machine Learning Engineer - User Journey
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning, especially those related to user journey optimisation. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Engage with the machine learning community by attending meetups or webinars. Networking with professionals in the industry can provide insights into what companies like us are looking for and may even lead to referrals.
✨Tip Number 3
Brush up on your Python and experience with frameworks like Pytorch and TensorFlow. Be prepared to discuss specific projects where you've implemented these technologies, as practical examples can set you apart from other candidates.
✨Tip Number 4
Understand our company culture and values. Research how we approach machine learning and personalisation at StudySmarter, and be ready to share how your own values align with ours during the interview process.
We think you need these skills to ace Junior Machine Learning Engineer - User Journey
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly any hands-on projects or roles that demonstrate your skills in Python, Scala, or similar languages. Emphasise your familiarity with tools like Pytorch and TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with the goals of the company. Mention specific projects or experiences that showcase your ability to contribute to the team’s objectives, such as optimising user journeys or developing GenAI prototypes.
Showcase Your Projects: If you have worked on relevant projects, consider including a portfolio or links to your work. Highlight any machine learning systems you’ve implemented, especially those that had a measurable impact on business metrics.
Prepare for Technical Questions: Be ready to discuss your understanding of machine learning theory and practice during interviews. Prepare to explain the intuition behind your approaches and any assumptions made in your previous projects.
How to prepare for a job interview at Spotify
✨Showcase Your ML Knowledge
Be prepared to discuss your understanding of machine learning theory and practice. Highlight specific projects where you've implemented ML solutions, and be ready to explain the intuition behind your choices.
✨Demonstrate Collaboration Skills
Since the role involves working with a multi-disciplinary team, share examples of how you've successfully collaborated with others in past projects. Emphasise your ability to communicate complex ideas clearly to non-technical team members.
✨Familiarity with Tools and Technologies
Make sure to mention your hands-on experience with relevant programming languages like Python or Scala, as well as frameworks like Pytorch or TensorFlow. If you have experience with cloud platforms such as GCP or AWS, be sure to highlight that too.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving skills. Practice explaining your thought process when tackling challenges, especially those related to optimising user experiences or building data pipelines.
