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Description The Music Catalog Quality team is seeking a passionate and talented Machine Learning Engineer (MLE) to join us. The Music Catalog Quality team is on a mission to enable accurate, complete, and enriched music metadata and content across the Amazon Music catalog. Our team is responsible for detecting, correcting, and enriching catalog metadata in real-time, leveraging technologies such as large language models (LLMs), computer vision, natural language processing, deep learning classifiers, and related methods. Our mission is to provide high-quality, dynamically validated and enriched catalog metadata with low latencies across the Amazon Music experience. We automate the detection and correction of metadata anomalies, including misattributed tracks, duplicate content, incorrect artist information, and incomplete album details, while providing internal teams with the tools and flexibility to continuously improve catalog integrity at scale. Key job responsibilities Design, build, and operate scalable machine learning pipelines and online serving systems Work closely with applied scientists to optimize ML model performance and implement end-to-end solutions from experimentation through production Drive technology choices and continuous innovation for ML infrastructure across the sponsored products organization Collaborate with product managers, scientists, and engineers to deliver the right product for customers Build and maintain strong relationships across partner disciplines (Product, Science and Engg) to ensure customer-focused delivery Contribute to operational excellence - monitoring, troubleshooting, and supporting high-volume, low-latency systems Basic Qualifications 3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience Experience working with PyTorch or JAX software 2+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience Preferred Qualifications 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Master's degree in computer science or equivalent Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques 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. Company - Amazon Development Centre (India) Private Limited Job ID: A10486419
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.