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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Machine Learning Compiler Engineer, AWS Neuron, Annapurna Labs - **Company:** Amazon.com, Inc. - **Location:** Austin, TX, United States - **Experience:** Expert - **Salary:** $193,300.0 - $261,500.0 - **Contract:** Internship / Graduate position - **Skills:** Amazon Alexa, Amazon Web Services, Code Review, Computer Programming, Software Design Patterns, Hardware Design, Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Pytorch, Information Technology, Bare Metal, Build Process, Software Coding, Autodesk Autocad, Software Version Control, Programming Languages - **Published:** August 24, 2026 - **Apply:** https://dejobs.org/x/x/66224E273A8E43F9BCE6004C157F6ECC/job/ ## About the Role * 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 * 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 The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. Trainium delivers best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, the Neuron Kernel Interface (NKI) compiler, and a runtime that natively integrates into popular ML frameworks such as PyTorch and JAX. Neuron Kernel Interface (NKI) is a bare-metal language and compiler for directly programming NeuronDevices available on AWS Trainium instances. You can use NKI to develop, optimize, and run new operators directly on NeuronCores while making full use of available compute and memory resources. Explore NKI: https://awsdocs-neuron.readthedocs-hosted.com/en/latest/nki/index.html AWS Neuron is used at scale by customers such as Epic Games, Snap, Airbnb, Autodesk, Amazon Alexa, and Amazon Rekognition, along with many others across a range of segments. The Team: The Amazon Annapurna Labs team is responsible for building innovative silicon and software for AWS customers. We are at the forefront of innovation, combining cloud scale with the world's most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. With such breadth of talent, there is opportunity to learn all of the time. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. When you couple that with the ability to work on so many different products and services, it makes for a unique learning culture. Learn more about our history: https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success You: As a Sr. Machine Learning Compiler Engineer on the NKI team, you will be a thought leader supporting the ground-up development and scaling of a compiler that handles the world's largest ML workloads. Architecting and implementing business-critical features, publishing cutting-edge work, and mentoring a team of experienced engineers is what excites and challenges you. You will leverage your technical communication skills as a hands-on partner to AWS ML teams. A background in machine learning and AI accelerators is preferred, but not required. In order to be considered for this role, candidates must be currently located in or willing to relocate to Seattle, Cupertino, or Austin. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Single Server, Global Reach: Running a Worldwide Marketplace on Bare Metal in a Cloud-Dominated World](https://www.wearedevelopers.com/videos/1206-single-server-global-reach-running-a-worldwide-marketplace-on-bare-metal-in-a-cloud-dominated-world) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters)