Job Information
Amazon Senior Engineer Edge AI Infrastructure & Tooling , Device OS in Bengaluru, India
Description
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 and innovative products.
• Investigate and prototype edge computing solutions with AI integration capabilities
• Develop backend integrations for various SoC vendors and AI accelerators
• Build developer tools including profilers, debuggers, model converters, and bench marking suites
• Optimize model deployment workflows and performance for resource-constrained environments
• Create SDKs, APIs, and documentation to enable seamless developer experiences
• Create automated testing frameworks for model accuracy and performance validation
• Collaborate with ML researchers to bridge the gap between research and production
• Work in an Agile/Scrum environment to deliver high quality software
• Establish architectural principles and mentor team members
About the team
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.
Basic Qualifications
5+ years of non-internship professional software development experience
Experience in embedded development in C/C+- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
5+ years in ML tooling and dev/prod infrastructure
Proven experience working with edge hardware platforms (Qualcomm, MediaTek, NVIDIA Jetson, Apple Neural Engine, etc)
Experience with edge AI inference frameworks (PyTorch, ExecuTorch, TensorFlow Lite, ONNX Runtime, etc.)
Proficiency with model optimization techniques: quantization (INT8, FP16, mixed-precision), pruning, knowledge distillation
Experience with model formats (.tflite, .onnx, .pt, .trt, FlatBuffers) and conversion pipelines
Experience deploying and tuning LLMs using techniques like LoRA, QLoRA, and instruction tuning
Strong coding skills with the ability to implement custom optimized kernels
Preferred Qualifications
5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience deploying LLMs or advanced ML models on resource-constrained devices
Experience with MLOps practices, automated model testing, model production (deployment, CI/CD, monitoring) and operationalizing LLMS & ML models at scale
Familiarity with heterogeneous computing and workload scheduling across CPU/GPU/NPU
Experience with real-time systems, latency-critical applications, and deterministic inference
Background in SDK development, developer tooling, and creating exceptional developer experiences
Virtual platform development and cloud deployment
Strong cross-functional leadership, with the ability to influence product roadmaps and technical strategy across organizations
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.