Applied Scientist, Amazon Music - Catalog Quality

Amazon is hiring an Applied Scientist, Amazon Music - Catalog Quality in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The posting mentions Python, PyTorch and TensorFlow among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design and develop end-to-end machine learning and generative AI systems for Amazon Music catalog quality.

PythonPyTorchTensorFlowLLMs

computer-visionnlpmachine-learningdeep-learningnatural-language-processinggenerative-ai

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. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music.

The Music Catalog Quality team at Amazon Music serves a key role in developing solutions to ensure and improve the quality of catalog metadata and content across the music streaming experience. We create solutions that detect, measure, and remediate quality issues in music metadata - including artist information, track attributes, versions, content tags, and provide actionable insights that enable continuous improvement of the catalog. We leverage a host of scientific and engineering technologies to accomplish this mission, including Generative AI, classical ML, Natural Language Processing, Computer Vision, and automated data validation pipelines.

Key job responsibilities
As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Other responsibilities include:

- Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks.
- Use machine learning, deep learning, LLMs and Agentic AI techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes
- Design, development and evaluation of AI models for predictive learning
- Research and implement novel machine learning and statistical approaches
- Implement scalable data pipelines and model-serving systems.
- Analyze experimental results, draw insights, and refine models to improve accuracy and robustness.
- Communicate findings and recommendations to technical and non-technical audiences.

Basic qualifications

- 3+ years of building models for business application experience
- PhD, or Master's 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

Preferred qualifications

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Applied Scientist, Amazon Music - Catalog Quality at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied Scientist, Amazon Music - Catalog Quality is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN, KA, Bengaluru.
The job was posted on August 21, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPMachine learningDeep learningNatural Language ProcessingGenerative AIPythonPyTorch

Also common in applied scientist jobs at this level

Reinforcement learning TensorFlow Spark AWS scikit-learn PyTorch

Pay

Typical applied scientist job: $167k

This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where natural language processing was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, Machine learning, Deep learning, and Natural Language Processing. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

Get your CV reviewed before you apply

Send your CV and the role you want next. Your review arrives by email within 3 days.

Get a free CV review Check your resume with the ATS resume checker