Staff Machine Learning Engineer, Spotify
Content & Catalog Management
More information about location
Commercial music streaming service
Open for applications
Commercial music streaming service
1001+ employees
Open for applications
More information about location
1001+ employees
Company mission
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 opportunity to enjoy and be inspired by it
Role
Who you are
- You have a proven track record of creating, promoting and growing ML strategy for platforms and have used it to deliver horizontal solutions to vertical problems
- You have hands-on experience in implementing ML systems at scale in Java, Scala, Python or similar and also with ML-specific libraries and frameworks like TensorFlow, PyTorch or similar
- You have in-depth knowledge of various ML algorithms, including supervised, unsupervised, and reinforcement learning, and have experience with algorithm selection, tuning, and evaluation
- You have deep experience communicating sophisticated ML practices, solutions and algorithms to technical and non-technical parties unfamiliar with ML terminology and principles. You see this educational opportunity as a key part of your role and always seek to help others understand and learn
- You have shown experience in leading ML projects and mentoring more inexperienced engineers, and driving technical strategy and decision-making within teams
- You have experience with containerization and orchestration tools like Docker and Kubernetes
- You have experience with cloud platforms such as GCP, AWS, or Microsoft Azure, and familiarity with cloud-based ML services and tools, such as Google AI Platform, AWS SageMaker or Azure Machine Learning
- You are comfortable writing queries, exploring data, and collaborating on hypotheses with product and engineering counterpart
- You have knowledge of model deployment techniques and serving frameworks like TensorFlow Serving, TorchServe, or custom APIs
What the job involves
- We are seeking a Machine Learning (ML) Staff Engineer eager to own the definition, adoption and expansion of ML usage within our content and catalogue management platform
- You’ll work with a community of engineers, researchers, product managers, designers and data scientists with varied levels of exposure and experience in ML
- The Content and Catalog Management (CoCaM) team works at the heart of the Content Platform R&D studio, the central point for the ingestion, distribution, management, knowledge and growth of all content you experience through Spotify products
- In CoCaM, we drive the management of content and make decisions that impact the whole of Spotify on all contents appropriateness, availability, quality and accuracy
- Through reactive and proactive reporting mechanisms we use the knowledge of Content Platform and apply platform & business policy with content, user, financial and experiential context to make and store a decision best for Creators, Consumers and Spotify
- Together with the CoCaM Engineering Lead, Content Platform Engineering Leadership and fellow Staff Engineers; you’ll own the expansion of CoCaM ML knowledge and expertise, and collaborate to find opportunities for more efficient, effective and consistent use of ML in our decision-making pipeline
- Own the ML strategy for content and catalog management across six squads. Ensure the platform can support diverse content types, policies, provides data for reporting and auditability and enables the right balance of fast and accurate decisions
- Enhance the ML competence among 40+ engineers, engineering managers and product managers. Provide mentorship on the usage of ML with traditional engineering approaches to use the right solution for the right problem
- Partner with Staff Engineers and Product partners, policy owners and operational teams, to identify and demonstrate ML opportunities. Encourage critical thinking within teams to develop this understanding themselves
- Cultivate strong relationships within the CoCaM Staff Engineers, Engineering Managers and Product Managers and promote the culture of collaboration, openness and inclusion to develop more well-rounded solutions
- Promote experimentation and iteration to encourage more out-of-the-box approaches to engineering problems that we face and balance the need to deliver on the outcomes and goals we’re committed to
- Drive technical decisions and standard methodologies in ML to ensure high-quality and scalable solutions are built by our engineers
- Stay updated with the latest ML advancements and Spotify ML standards and develop a learning environment to continuously improve the team's skills and knowledge
Our take
Spotify was founded in an attempt to combat the rampant music piracy that was causing significant harm to the industry. The company has since taken music streaming mainstream and now has 180m+ paying subscribers across the world.
With features that include a highly accessible interface and a vast catalogue of artists, Spotify's strong brand has been able to maintain growth in spite of fierce competition from deep-pocketed rivals like Amazon and Apple. The company has achieved this by making smart acquisitions to move into other verticals to strengthen its offerings, especially podcasting, by acquiring Gimlet Media, Anchor and Parcast.
Spotify's future plans include rapid growth with a goal to become a one-stop destination for all digital sound, as well as AI and NFT integrations. However, high costs incurred from the acquisition of exclusive podcasts, increasing competitor strength, and weak bottom-line growth mean that the company must find a balance to maintain its position in the sector.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
23% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jan 2016
$1bn
CONVERTIBLE
Jun 2015
$526m
SERIES G
Total funding: $2.1bn
Company benefits
- 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 - fully paid - 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
Company values
- Innovative: We move fast and take big risks
- Sincere: We have no time for internal politics
- Passionate: We revel in what we do
- Collaborative: We recognise that we're all in this together
- Playful: We don't take ourselves too seriously
Company HQ
Norrmalm, Stockholm, Stockholms län
Articles
Leadership
Daniel Ek
(CEO & Chairman)Founded Spotify in 2006. Previously worked as an executive at Tradera, an auction company that was sold to eBay and was briefly the CEO of uTorrent.
People progressing
Joined as a Conversion Manager in the Growth Team. Promoted three times over seven years to Senior Director - Head of Growth.
Joined as a Customer Advisor. Since then has had the role titles Senior Advisor, Content Associate, Team Coach, and Operations Manager - Primary Support. Hurst is now currently the Business Operations Manager of Music.
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