Applied Scientist-II, Amazon Music Search Science, Amazon Music – Search Science

Amazon Music is an immersive audio entertainment service that deepens connections between fans artists and creators. From personalized music playlists to exclusive podcasts concert livestreams to artist merch Amazon Music is innovating at some of the most exciting intersections of music and culture.

The Amazon Music Search Science team is seeking an innovative and driven Applied Scientist to join our engineering and science hub in Bangalore. You will work alongside a world-class team of machine learning experts to break new ground in understanding user intent classifying complex audio and musical forms and creating next-generation interactive search experiences that help users find the exact music podcasts and audio content they are in the mood for.

In this role you will own the design development and deployment of end-to-end machine learning systems. You will balance execution on core search and discovery prioritiessuch as improving retrieval accuracy latency and relevance for millions of daily querieswhile laying the foundational modeling capabilities for broader semantic understanding and advanced conversational search experiences across mobile web and voice-forward devices (like Alexa and Echo).

Key job responsibilities
- Core Search & Execution: Collaborate with scientists software engineers and product managers to define frame and solve complex business and ranking problems as machine learning information retrieval or optimization tasks.
- Advanced AI & Modeling: Design build train and evaluate production-grade ML models using classical machine learning deep learning Large Language Models (LLMs) and Agentic AI techniques to scale music discovery and intent resolution.
- End-to-End Production Ownership: Take algorithms from research ideation to production deployment. Build scalable data pipelines efficient model-serving systems and robust offline/online evaluation frameworks.
- Experimentation & Iteration: Design and analyze large-scale A/B experiments across millions of customers to measure impact on search relevance engagement and customer satisfaction refining models for continuous improvement.
- Forward-Looking Innovation: Research and implement novel statistical and machine learning approaches exploring multi-modal understanding rich content semantics and advanced retrieval mechanisms that extend beyond traditional search boundaries.
- Technical Communication: Communicate findings architectural decisions and technical roadmaps clearly to both technical peers and executive stakeholders authoring robust design documents and contributing to team standards.

Basic Qualifications
- PhD or Masters degree and 4 years of relevant experience in Computer Science Computer Engineering Machine Learning Statistics or a related quantitative field.
- 3 years of hands-on experience building machine learning models or algorithms for business applications and deploying them into production.
- Strong programming skills in Python Java C or related languages with a solid foundation in data structures algorithms and object-oriented design.
- Experience in one or more of the following areas: Information Retrieval Natural Language Processing (NLP) Recommender Systems Deep Learning or Numerical Optimization.
- Demonstrated ability to work effectively with cross-functional teams in a fast-paced environment.

Preferred Qualifications
- Experience with large-scale distributed computing frameworks and big data systems (e.g. Spark Hadoop AWS infrastructure).
- Experience building search ranking query understanding or semantic retrieval systems for high-scale consumer applications.
- Familiarity with modern foundation models LLMs fine-tuning techniques and efficient inference optimization for production services.
- Track record of peer-reviewed publications or patents at top-tier machine learning/AI conferences (e.g. NeurIPS KDD ACL SIGIR ICML).
- Experience in designing executing and evaluating rigorous online A/B experiments.

- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience using Unix/Linux
- PhD in computer science machine learning engineering or related fields

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