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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. MLE, Prime Video ML Platform - **Company:** Amazon.com, Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $193,300.0 - $261,500.0 - **Contract:** Internship / Graduate position - **Skills:** Clean Code Principles, Code Review, Computer Programming, Software Design Patterns, Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Pytorch, Large Language Models, Information Technology, Optimization Algorithms, Build Process, Machine Learning Operations, TensorRT, Software Coding, Software Version Control, Programming Languages - **Published:** July 19, 2026 - **Apply:** https://dejobs.org/x/x/BF1BD70ADE2044A7BFFBC1EB824EC2A0/job/ ## About the Role We are looking for a self-motivated, passionate and resourceful Senior Software Development Engineer to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will be a technical leader helping to design and build the ML infrastructure that power our vision. You will tackle complex and ambiguous problems, designing and delivering scalable and resilient ML platform solutions from the ground up. You will not only write high-quality, maintainable code, but also mentor other engineers, influence our technical strategy, and drive engineering best practices across the team. Your work will directly contribute to making Prime Video's operations more efficient and will set the technical foundation for years to come., * 5+ years of non-internship professional software development experience * 5+ years of programming with at least one software programming language experience * 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience * Experience as a mentor, tech lead or leading an engineering team * Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT * Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques, * 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience * Bachelor's degree in computer science or equivalent ## Description Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports - including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads., * Building ML platform services with Tier-1 availability and performance characteristics while enabling rapid model iteration and experimentation for scientists. * Evolving the model serving and feature delivery infrastructure to enable continuous experimentation and keep pace with innovations in state-of-the-art ML capabilities. * Designing and scaling training pipelines, real-time inference systems, and feature stores that support the constantly evolving landscape of Prime Video personalization across Movies, TV Shows, Live Sports, Linear TV, and beyond. * Leading and partnering on developing the strategic technical vision for the PV ML Platform, including model lifecycle management, online/offline evaluation, and serving optimization. * Partnering with Scientists, Product Managers, and Engineering stakeholders to translate research breakthroughs into production-grade platform capabilities. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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