Staff Machine Learning Engineer - Customer Service Platform

The Freemium R&D team oversees the entire user journey on Spotify and ensures we engage with people in innovative ways, every step of the way. Our team grows Spotify’s audience by finding future listeners around the world and delivering the right value to them, at the right time. With research, product development, product design, engineering, and marketing all collaborating in one organization, we’re able to quickly create meaningful features and services for millions of people around the world, resulting in joyful, long-lasting relationships with Spotify.
We are looking for a Staff Engineer with experience in building sophisticated machine learning models and infrastructure to join Customer Service Platform, a collection of 5 teams that is redefining how to make Customer Service Easy at Spotify, by providing our customers with help that's easy to find, advisors with tools that are easy to use, and other product development teams with SDKs and APIs that are easy to integrate to our platform.
We are looking for a technical leader that relentlessly advocates for customers, feels comfortable working across team boundaries, and is not afraid to take on responsibility to lead strategic projects. In this role, this person will build complex data infrastructure to gather signals from all across Spotify, and machine learning models to understand language and behavioural patterns that makes getting help easy when things go wrong, so our listeners can go back to enjoying our product.

What You'll Do:

• Own the technical vision and execution of Contact Intent Detection Platform: a machine learning system at the heart of understanding root causes why customers contact Spotify to get help.
• Define a 3-year data and machine learning strategy for the area in collaboration with the engineering manager of the team.
• Build systems to optimise a $XX million cost budget through the systems you build, while preventing customer churn and improving customer experiences in collaboration with our partner growth-oriented organisations.
• Participate in our Technical Steering Group in CS Platform – a group of individual contributors that drives engineering excellence across our organisation.
• Influence other staff+ engineers to craft the direction of other platforms in our parent organisation.
• Coordinate strategic technical projects across our 5 squads in Customer Service Platform and other teams across Spotify as a technical leader.
• Collaborate with team members to determine how to craft scalable systems, fabulous customer experiences, and sophisticated machine learning systems that help other teams to meet their Customer Service needs.
• Partner up with our vendors and 3rd-party providers to ensure we buy outstanding vendor software, and build strategic capabilities in-house;
• Collaborate with engineering managers, product managers, data scientists, user researchers and designers to identify and solve meaningful problems inside and outwards of the Customer Service domain.

Who You Are:

• You have a strong track record in building innovative Natural Language Processing Machine Learning systems which also leverage behavioural data to address highly ambiguous and complex challenges;
• You have strong foundational knowledge in statistics and know how to collaborate closely with data stakeholders such as data scientists and researchers;
• You are a great communicator. You can explain complex topics in simple terms to audiences ranging from executives and specialists;
• You have experience in building modern data and ML infra using technologies such as TensorFlow, SciKit learn, Dataflow, Hadoop, Scalding, Spark, Storm, Scio.
• You enjoy working in an environment where you constantly experiment and iterate quickly in collaboration with design, data science and user research teams.
• You know how to partner up with product and engineering managers to shape products, trim down scope where needed, and build systems to achieve business outcomes;
• You have a deep understanding of system design, data structures, and algorithms.
• You care about quality and you know what it means to ship high quality code.
• You know the importance of building strong relationships with colleagues and partners, and always put the customer's needs first.
• You enjoy mentoring and growing other engineers by providing technical guidance and interpersonal advice.
• Customer Service domain experience is not needed, but is a plus.

Where You'll Be:

• We are a distributed workforce enabling our band members to find a work mode that is best for them!
• Where in the world? For this role, it can be within the Americas region in which we have a work location: https://lifeatspotify.com/locations
• We ask that our team members be located within Central Standard time zone, Eastern Standard time zone, or Brasília time zone for the purposes of our collaboration hours
• Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
• Working hours? We operate within the Eastern Standard time zone for collaboration

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
Spotify transformed music listening forever when we launched in 2008. 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 world’s most popular audio streaming subscription service.