Backend Engineer - Learning Infrastructure

As a Backend Engineer - Learning Infrastructure at Spotify, your key responsibilities include identifying collaboration opportunities, mentoring other engineers, delivering complex tasks on time, and managing dependencies across multiple teams. You will develop backend systems at scale and ensure they are optimized for performance. Additionally, you will play a critical role in considering inter-squad connections within the larger machine learning ecosystem, facilitating seamless interactions between features.

To qualify for the Backend Engineer - Learning Infrastructure role at Spotify, you should have at least 3 years of hands-on experience in implementing production machine learning infrastructure, preferably using languages like Python, Java, or Scala. A solid understanding of data processing concepts, experience with agile software development processes, and proficiency in modular code design are also essential for this position. Your experience with developing and optimizing backend systems at scale will set you apart.

Essential skills for the Backend Engineer - Learning Infrastructure at Spotify include expertise in backend development with a focus on performance optimization, deep knowledge of machine learning infrastructure, and a collaborative mindset to work effectively with cross-functional teams. Additionally, mentoring skills are valuable for helping your peers grow, and a solid understanding of agile processes will be beneficial in managing your projects effectively.

Yes, the Backend Engineer - Learning Infrastructure position at Spotify offers flexibility in terms of remote work. While you will be required to attend some in-person meetings in Stockholm 2-3 times per week, the role allows you the freedom to work from home or anywhere else that enables you to be most productive. This balance ensures you can tailor your work environment to suit your needs while contributing effectively to the team.

Spotify is committed to the career development of its Backend Engineers in Learning Infrastructure by providing mentoring opportunities, encouraging collaboration across teams, and promoting a culture of continuous learning. As a Backend Engineer, you’ll have the chance to take on large, complex tasks and drive solutions that influence the broader machine learning ecosystem, allowing you to grow your expertise while contributing to impactful projects.

When answering this question, focus on specific projects where you implemented or advanced machine learning infrastructure. Describe the technologies you used, the challenges faced, and how you optimized the systems. Highlight any key contributions you made to productionizing models and scaling infrastructure.

In your response, emphasize how effective data processing is foundational to building scalable backend systems. Discuss methodologies you've utilized for data ingestion, storage, and processing, and how these affect system reliability and performance.

Share your strategies for project management, such as breaking tasks into manageable parts, utilizing Agile methodologies, and setting realistic timeframes. Discuss how you communicate status updates and collaborate with your team to maintain alignment and accountability.

Detail your approach to mentoring, including providing constructive feedback and sharing knowledge about best practices in coding and project management. Illustrate how you create a supportive environment that encourages questions and fosters growth.

Discuss the programming languages you're experienced with, like Python, Java, or Scala, and provide examples of specific projects or pieces of work where you utilized these languages. Highlight any frameworks or tools that enhanced your productivity.

Talk about your habits for continuous learning, such as attending workshops, webinars, participating in online courses, or engaging in community forums. Mention any specific publications or influencers you follow in backend development and machine learning.

Describe your familiarity with Agile methodologies, including how you've implemented Agile practices, participated in sprints, and contributed to retrospectives. Provide examples of how Agile processes improved your team's efficiency and collaboration.

Share a specific issue you encountered and walk through your process of identifying the problem, analyzing potential solutions, and implementing the best course of action. Highlight the positive outcomes and any skills you developed in the process.

Explain your methods for maintaining open lines of communication, such as regular updates, collaborative tools, and adjusting your approach based on team needs. Stress the importance of understanding team roles and how this impacts project timelines.

Articulate your passion for technology and how it aligns with Spotify’s mission. Mention specific aspects of Spotify's culture, projects in machine learning, or the technologies they use that attract you to the company. Convey how your experience and goals sync up with the role.