Senior Software Engineer - Edge AI Platform, Device OS

Overview

Are you passionate about bringing state of the art AI technology to edge devices? Join Amazon's Device OS organization, where we're revolutionizing how AI powers everyday devices. We're seeking exceptional Senior Software Development Engineers who can help us push the boundaries of edge computing and artificial intelligence. This is your chance to shape the future of AI-enabled devices that impact millions of customers worldwide.

Key job responsibilities

As a Sr. Software Development Engineer, you will conceive, design and deliver innovative features for Amazon devices. You will be responsible for architecting and developing software solutions for new confidential products.

• Investigate and prototype edge computing solutions with AI integration capabilities
• Work in an Agile/Scrum environment to deliver high quality software
• Establish architectural principles and mentor team members
  
  

6062325 Senior Engineer Edge AI Infrastructure Tooling , Device OS ![CDATA[ p strong em This job is with Amazon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. /em /strong /p pstrongDESCRIPTION:/strong/ppAre you passionate about bringing state of the art AI technology to edge devices? Join Amazon's Device OS organization, where we're revolutionizing how AI powers everyday devices. We're seeking exceptional Senior Software Development Engineers who can help us push the boundaries of edge computing and artificial intelligence. This is your chance to shape the future of AI-enabled devices that impact millions of customers worldwide.br/br/br/Key job responsibilitiesbr/As a Sr. Software Development Engineer, you will conceive, design and deliver innovative features for Amazon devices. You will be responsible for architecting and developing software solutions for new and innovative products.br/br/

• Investigate and prototype edge computing solutions with AI integration capabilities br/
• Develop backend integrations for various SoC vendors and AI accelerators br/
• Build developer tools including profilers, debuggers, model converters, and bench marking suitesbr/
• Optimize model deployment workflows and performance for resource-constrained environments br/
• Create SDKs, APIs, and documentation to enable seamless developer experiencesbr/
• Create automated testing frameworks for model accuracy and performance validationbr/
• Collaborate with ML researchers to bridge the gap between research and productionbr/
• Work in an Agile/Scrum environment to deliver high quality software br/
• Establish architectural principles and mentor team members br/br/About the teambr/The Device OS Team builds Edge AI/ML frameworks enabling partners to launch applications, services, and devices customers love. We develop unified inference platforms that connect advanced AI models with diverse hardware ecosystems across multiple SoC platforms. Our infrastructure and tooling empower developers to deploy, optimize, and monitor high-performance AI models on edge devices.br//ppstrongBASIC QUALIFICATIONS:/strong/pp- 5+ years of non-internship professional software development experiencebr/- Experience in embedded development in C/C++br/- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experiencebr/- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruningbr/- 5+ years in ML tooling and dev/prod infrastructurebr/- Proven experience working with edge hardware platforms (Qualcomm, MediaTek, NVIDIA Jetson, Apple Neural Engine, etc)br/- Experience with edge AI inference frameworks (PyTorch, ExecuTorch, TensorFlow Lite, ONNX Runtime, etc.)br/- Proficiency with model optimization techniques: quantization (INT8, FP16, mixed-precision), pruning, knowledge distillationbr/- Experience with model formats (.tflite, .onnx, .pt, .trt, FlatBuffers) and conversion pipelinesbr/- Experience deploying and tuning LLMs using techniques like LoRA, QLoRA, and instruction tuningbr/- Strong coding skills with the ability to implement custom optimized kernels/ppstrongPREFERRED QUALIFICATIONS:/strong/p- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experiencebr/- Experience deploying LLMs or advanced ML models on resource-constrained devicesbr/- Experience with MLOps practices, automated model testing, model production (deployment, CI/CD, monitoring) and operationalizing LLMS ML models at scalebr/- Familiarity with heterogeneous computing and workload scheduling across CPU/GPU/NPUbr/- Experience with real-time systems, latency-critical applications, and deterministic inferencebr/- Background in SDK development, developer tooling, and creating exceptional developer experiencesbr/- Virtual platform development and cloud deploymentbr/- Strong cross-functional leadership, with the ability to influence product roadmaps and technical strategy across organizationsbr/br/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.]] Software Development Internet Full-time Bengaluru India IN https://mygwork.com/jobs/amazon-senior-engineer-edge-ai-infrastructure-tooling-device-os?src=linkedinutm_source=linkedinutm_medium=referralutm_campaign=jobs Amazon ![CDATA[ p strong em This job is with Amazon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. /em /strong /p pstrongDESCRIPTION:/strong/ppAre you passionate about bringing state of the art AI technology to edge devices? Join Amazon's Device OS organization, where we're revolutionizing how AI powers everyday devices. We're seeking exceptional Senior Software Development Engineers who can help us push the boundaries of edge computing and artificial intelligence. This is your chance to shape the future of AI-enabled devices that impact millions of customers worldwide.br/br/br/Key job responsibilitiesbr/As a Sr. Software Development Engineer, you will conceive, design and deliver innovative features for Amazon devices. You will be responsible for architecting and developing software solutions for new and innovative products.br/br/
• Investigate and prototype edge computing solutions with AI integration capabilities br/
• Develop backend integrations for various SoC vendors and AI accelerators br/
• Build developer tools including profilers, debuggers, model converters, and bench marking suitesbr/
• Optimize model deployment workflows and performance for resource-constrained environments br/
• Create SDKs, APIs, and documentation to enable seamless developer experiencesbr/
• Create automated testing frameworks for model accuracy and performance validationbr/
• Collaborate with ML researchers to bridge the gap between research and productionbr/
• Work in an Agile/Scrum environment to deliver high quality software br/
• Establish architectural principles and mentor team members br/br/About the teambr/The Device OS Team builds Edge AI/ML frameworks enabling partners to launch applications, services, and devices customers love. We develop unified inference platforms that connect advanced AI models with diverse hardware ecosystems across multiple SoC platforms. Our infrastructure and tooling empower developers to deploy, optimize, and monitor high-performance AI models on edge devices.br//ppstrongBASIC QUALIFICATIONS:/strong/pp- 5+ years of non-internship professional software development experiencebr/- Experience in embedded development in C/C++br/- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experiencebr/- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruningbr/- 5+ years in ML tooling and dev/prod infrastructurebr/- Proven experience working with edge hardware platforms (Qualcomm, MediaTek, NVIDIA Jetson, Apple Neural Engine, etc)br/- Experience with edge AI inference frameworks (PyTorch, ExecuTorch, TensorFlow Lite, ONNX Runtime, etc.)br/- Proficiency with model optimization techniques: quantization (INT8, FP16, mixed-precision), pruning, knowledge distillationbr/- Experience with model formats (.tflite, .onnx, .pt, .trt, FlatBuffers) and conversion pipelinesbr/- Experience deploying and tuning LLMs using techniques like LoRA, QLoRA, and instruction tuningbr/- Strong coding skills with the ability to implement custom optimized kernels/ppstrongPREFERRED QUALIFICATIONS:/strong/p- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experiencebr/- Experience deploying LLMs or advanced ML models on resource-constrained devicesbr/- Experience with MLOps practices, automated model testing, model production (deployment, CI/CD, monitoring) and operationalizing LLMS ML models at scalebr/- Familiarity with heterogeneous computing and workload scheduling across CPU/GPU/NPUbr/- Experience with real-time systems, latency-critical applications, and deterministic inferencebr/- Background in SDK development, developer tooling, and creating exceptional developer experiencesbr/- Virtual platform development and cloud deploymentbr/- Strong cross-functional leadership, with the ability to influence product roadmaps and technical strategy across organizationsbr/br/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.]]