Staff Machine Learning Engineer - Freemium
New York City
Applications have closed
Spotify
We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!We are looking for a Staff Machine Learning Engineer within the Freemium mission who will work on providing the right value to the right user at the right time. We seek to customize the Spotify experience to fit each of our users expectations, creating an engaging experience and growing the Spotify audience. We use machine learning to customize this experience at the key moments of interaction through the user journey. It is a highly impactful space within R&D and a highly engaged team. This is a role that will allow you to play a key role in evolving our product to the next level!
What you'll do
- Support the engineering team in formulating the technical vision and strategy for our ML-based optimization across the freemium funnel.
- Seek sophisticated data-related problems involving some of the most diverse datasets available and resolve feasibility of projects through quick prototyping with respect to performance, quality, time and cost using Agile methodologies
- Architect outstanding infrastructure (platforms, tools, and approaches) to accelerate our research and prototypes to the product phase and set up efficient training, deployment, optimization, and testing of models.
- Apply machine learning to build product features that drive tangible business impact
- Be a leading voice in an active community of ML practitioners across Spotify and improve existing state-of-the-art tooling in the Spotify ecosystem (TensorFlow, DataFlow, python-beam, Google Cloud Platform)
- Contribute to our team-wide product conceptualization in collaboration with engineers, researchers, product managers and tech leads on the team.
- Help drive optimization, testing and tooling to improve data quality
Who you are:
- PhD or M.Sc. in Machine Learning, or related field
- You have 4+ years of machine learning product development experience demonstrating large scale data processing technologies (e.g. TensorFlow, SciKit learn, Dataflow, Hadoop, Scalding, Spark, Storm)
- You have experience in using ML techniques to optimize customer facing product features
- You have a strong mathematical background in statistics and machine learning
- You care about agile software processes, data-driven development, reliability, and responsible experimentation
- You preferably have machine learning publications or work on open source to share with us
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 East Coast US or EMEA region in which we have a work location
- 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 Central European time zone for collaboration
- We ask that our team members be located within Eastern time zone, Greenwich Mean time zone, Central European time zone, or Eastern European standard time zone for the purposes of our collaboration hours
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Dataflow Data quality Engineering GCP Google Cloud Hadoop Machine Learning Open Source PhD Prototyping Python R R&D Research Scikit-learn Spark Statistics Streaming TensorFlow Testing
Perks/benefits: Equity Home office stipend
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