Top Benefits
Six months fully paid parental leave for new parents
Flexible public holidays, swap days off per values
Employee assistance program and self-care hub
About the role
Who you are
- You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes
- You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages
- Experience with PyTorch, Ray, Hugging Face and related tools is required
- You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
What the job involves
- We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with Spotify - and who make impactful changes to Home recommendation systems to achieve this goal
- As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
- Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
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
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Top Benefits
Six months fully paid parental leave for new parents
Flexible public holidays, swap days off per values
Employee assistance program and self-care hub
About the role
Who you are
- You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes
- You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages
- Experience with PyTorch, Ray, Hugging Face and related tools is required
- You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
What the job involves
- We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with Spotify - and who make impactful changes to Home recommendation systems to achieve this goal
- As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
- Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
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