Spotify
Machine Learning Engineer
Rol remoto de Machine Learning Engineer con fit claro de ubicación del candidato.
Publicado6 jul 2026
Países elegibles3 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
CanadáMéxicoEstados Unidos
Resumen del rol
Machine Learning Engineer
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
What You’ll Do
- 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.
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.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
- This team operates within the Eastern Standard time zone for collaboration.
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