Applied Scientist II role at Amazon Ads focusing on Sponsored Products and Brands, specifically the Search Ranking and Interleaving (R&I) team. The role involves developing and applying GenAI and ML techniques to optimize ad ranking, allocation, and relevance on the search page. Key responsibilities include building real-time ML algorithms for ad auctions, developing multi-objective optimization methods, and researching new ML approaches to improve shopper experience and drive revenue. The role requires experience in building models for business applications and applying theoretical models in practice.

Software Development Engineer focused on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Trainium and Inferentia). The role involves working with external and internal customers to identify obstacles and opportunities for accelerating adoption, and transforming service performance, durability, cost, and security.

Software Development Engineer focused on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Trainium and Inferentia). The role involves working with external and internal customers to identify obstacles and opportunities for accelerating adoption, and transforming service performance, durability, cost, and security.

Manager for Navigation Science team at Amazon Prime Air, focusing on developing advanced navigation algorithms and flight software for delivery drones. Requires leadership experience, strong programming skills, and experience with agile development. The role involves defining system architectures, contributing to flight algorithms, and driving innovation in a safety-critical environment.

Machine Learning Engineer role focused on optimizing and tuning inference performance for AWS Neuron accelerators, specifically for large language models (LLMs) and other key ML model families. The role involves developing and performance tuning building blocks for the distributed inference library, ensuring high performance and efficiency on Trn2 and Trn3 servers. Requires experience with LLM inference optimization, kernels, Python, PyTorch, or JAX.

Principal Engineer role at Amazon AWS Builder Acceleration focused on leveraging GenAI and advanced AWS technologies to simplify the software development, deployment, and maintenance lifecycle for AWS engineers. The role involves defining technical strategy, identifying high-impact problems, developing roadmaps, and pioneering AI-powered builder experiences at AWS scale.

This role is for a Senior SoC Power Engineer focused on developing and optimizing power consumption for machine learning accelerators (Inferentia and Trainium SoCs) within AWS. The engineer will be responsible for power analysis and modeling from RTL to netlist, identifying power saving opportunities, and correlating simulation results with lab measurements. This is an engineering role focused on the hardware infrastructure that powers AI workloads.

This role is for an AI Platform Builder, a Data Engineer focused on developing Platforms and Agentic AI solutions. The role involves designing, implementing, and maintaining data pipelines and platforms that power AI/ML initiatives, using AI for code generation, optimization, and building AI-native self-service data platforms. It emphasizes prompt-driven development and creating self-improving systems.

Software Engineering Manager to lead a team focused on machine learning compiler design and development for AWS Neuron, driving optimization techniques, hardware bring-up, and influencing pre-silicon design decisions to accelerate ML infrastructure.

Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology for supply chain optimization. The role involves managing a team of scientists, focusing on next-generation solutions for buying, placement, and fulfillment decisions, and translating customer needs into reusable software infrastructure. Key responsibilities include leading innovation in RL applications, building and developing a high-performing team, bridging technical possibilities with business requirements, and driving cross-functional collaboration.

Applied Scientist role focused on building machine learning models and technology to automatically monitor and classify billions of products in the Amazon catalog, ensuring compliance and safety. The role involves working with large datasets, deep learning for search matching and ranking, filtering, indexing, and document understanding, with a focus on delivering customer-facing experiences at Amazon scale.

The Machine Learning Compiler Engineer will work on the Amazon Neuron team to develop and scale a deep learning compiler stack for Amazon's custom ML accelerators (Inferentia and Trainium). This role involves optimizing neural network models for inference and training performance, integrating with ML frameworks, and contributing to the software stack that enables large-scale ML workloads. The engineer will be involved in pre-silicon design and bringing new features to market.

This role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-based generation, and human-in-the-loop approaches. The Senior Language Engineer will define data creation strategies, lead complex data collections, and analyze large datasets. They will also build tools for data analysis and creation, and collaborate with scientists to evaluate AI model performance.

This role involves developing bare metal firmware for custom ASIC-based ML Accelerator chips, focusing on hardware/software co-design for machine learning acceleration systems. The engineer will work on the firmware that drives neural network model execution on custom silicon, collaborating with hardware design teams. While no prior ML knowledge is required, the role is core to enabling ML infrastructure.

The role focuses on building and maintaining a Spark-based infrastructure for processing large multimodal datasets critical for machine learning research, specifically for state-of-the-art agents within the AGI Autonomy organization. It involves data extraction, transformation, and creating tooling for researchers, with a secondary focus on agent development.

Master's student internship focused on applying machine learning, NLP, computer vision, automated reasoning, or robotics to design and develop end-to-end systems for Amazon Science. The role involves working with large datasets, implementing systems, and potentially deploying solutions into production.

Senior Applied Scientist role focused on developing and launching end-to-end AI solutions, specifically recommendation systems leveraging generative models, for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, designing experiments, and collaborating with engineering and product teams to improve advertiser and shopper experiences.

Senior Software Development Engineer role focused on building Gen AI native games and gameplay experiences, and enhancing internal team productivity through agentic solutions. The role involves architecting, developing, and operating infrastructure for proprietary and third-party models, building intelligent agents, and optimizing AI solutions for performance and cost. It also includes leading internal GenAI adoption and ensuring enterprise-grade security and responsible AI.

This role focuses on validating next-generation machine learning accelerators for AWS, covering the entire vertical stack from silicon to system. The engineer will develop and execute validation strategies, conduct hands-on bring-up and debug, and collaborate with various teams to ensure the quality and performance of AI/ML accelerators used in AWS data centers for AI training and inference.

Data Scientist III on the Shopbop/Zappos Catalog Tech team responsible for designing and implementing ML approaches to improve product catalog data quality, automate data capture and classification, and integrate ML models into production systems. The role involves working with computer vision and NLP, and influencing product decisions through data-driven insights.

Senior Software Development Engineer to join the Gen AI & Strategic Initiatives team for Amazon Luna. The role involves architecting and building next-generation tools and platform infrastructure to support proprietary and third-party AI models, enabling Gen AI native games and enhancing internal team productivity through agents. Responsibilities include driving platform architecture, building scalable API infrastructure, launching cross-functional agents, optimizing performance, supporting developer experience, implementing observability, designing throttling systems, ensuring security and compliance, and driving operational excellence.

Senior Machine Learning Engineer role focused on developing and launching AI solutions for Prime Video's recommendation and personalization systems, utilizing deep learning, GenAI, and reinforcement learning. The role involves end-to-end ownership, experimental design, and collaboration with cross-functional teams to impact millions of customers.

This role focuses on enhancing the scalability, automation, and efficiency of large-scale training and real-time inference systems for Amazon Ads' Sponsored Products and Brands. The engineer will pioneer LLM inference infrastructure and work with applied scientists to optimize ML models and infrastructure, implementing end-to-end solutions. The team builds advanced ML models and infrastructure, from training to inference, including LLM-based systems, to deliver relevant ads.

Software Engineer role focused on building and optimizing the AWS Neuron compiler for custom AI chips (Inferentia and Trainium). The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized code for these accelerators, with a focus on large language models and diffusion models. Requires strong software engineering skills, particularly in C++, and experience with compiler technologies is preferred.

Manage a team of Applied Scientists, ML Engineers, and Software Development Engineers to develop science and engineering roadmaps for SPB ads CTR prediction using ML and Gen AI solutions. The role involves hiring, developing talent, and staying informed about scientific publications and industrial research trends. The team focuses on personalized shopping experiences through ML and GenAI solutions for response prediction and session-level understanding to optimize ad serving, targeting, sourcing, and bidding.

This role leads science and engineering for AI-powered sponsored product ads in offsite shopping experiences, focusing on generative AI and large-scale ML solutions. The goal is to revolutionize advertising by bridging human creativity with AI, impacting ad creation, optimization, performance analysis, and customer insights. The role involves extending campaigns to reach customers off-store and on third-party sites, working with external and internal partners, and driving results at scale with a GenAI-first approach. It requires significant experience in building large-scale ML/AI solutions and people management.

This role focuses on validating next-generation machine learning accelerators for AWS, covering the full vertical stack from silicon to system. The engineer will be responsible for developing validation strategies, executing test plans, debugging hardware and software, and collaborating with cross-functional teams to ensure the quality and performance of AI/ML accelerators used in AWS data centers.

The AGI team is seeking engineers to develop and maintain multi-modal and multi-lingual LLMs using scalable training and inference systems. The role involves deeply understanding technology landscapes, evaluating new technologies, and driving operational excellence. Key responsibilities include leading the design and automation of GenAI training compute infrastructure, mentoring engineers, identifying performance bottlenecks, and working with core AWS services, CI/CD pipelines, and Kubernetes.

Principal Applied Scientist role focused on building next-generation personalized shopping experiences at Amazon using LLMs, transformer models, and large-scale ranking systems. The role involves innovating features and models, leading science innovation, driving the science roadmap, and mentoring scientists. It aims to create a personalized shopping experience tailored to customer intent and product catalog understanding.

Senior Software Development Engineer at Amazon Annapurna Labs focused on leading a technical team to develop profiling and optimization tools for the Neuron ML accelerators fleet. The role involves working with hardware and software teams to identify bottlenecks and provide recommendations for improving performance of large ML workloads, including custom kernels.

This role focuses on developing diverse datasets for training and evaluating AI models, utilizing methods like synthetic data generation, model-supported generation, and human-in-the-loop collections. The Language Engineer will collaborate with cross-functional teams to innovate and advance the state-of-the-art in AI model evaluation and training.

Senior Applied Science Manager to lead AI initiatives for seller growth at Amazon. The role involves developing scientific models for customer demand, selection identification, and prioritization signals. It also includes leading the development of next-generation agentic experiences for sellers, integrating insights into products like ABA and OX, and driving business impact through ML/LLM solutions.

Senior Systems Engineer for Amazon Prime Air's autonomous drone perception systems. This role involves translating operational requirements into system specifications, bridging ML algorithms with flight control, and ensuring perception systems meet aviation certification standards. The focus is on the integration and validation of ML-based perception for safe autonomous flight.

Software Development Manager to lead a team optimizing LLMs for inference on AWS custom accelerators (Neuron, Trainium, Inferentia). Focus on improving model enablement speed, experience, usability, and quality through features, infrastructure, tools, and automation. Requires strong background in LLM architectures, performance optimizations, and distributed inference.

Senior Machine Learning Engineer role at Amazon Prime Video focused on developing and launching AI solutions for recommendation and personalization systems. The role involves end-to-end ownership of ML models, including design, implementation, experimentation (A/B testing), and deployment for millions of customers. It requires experience with large-scale ML systems and recommendation systems.

Software Development Engineer focused on ML Systems within Amazon Annapurna Labs, working on AWS Neuron software for ML chips (Inferentia and Trainium). The role involves building and applying AI agents to accelerate customer adoption of this technology, optimizing performance, durability, cost, and security for AWS customers.

Senior ML Kernel Performance Engineer for AWS Neuron SDK, focusing on optimizing deep learning and GenAI workloads on custom ML accelerators (Inferentia, Trainium). The role involves designing and implementing high-performance compute kernels, optimizing performance at the hardware-software boundary, and collaborating with customers and internal teams on model enablement and acceleration.

This role focuses on developing and launching end-to-end AI solutions for Prime Video's search and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The scientist will design and conduct experiments, collaborate with engineers and product managers, and publish research findings. The role is within the consumer domain, aiming to improve customer experience for millions of users.

Senior Machine Learning Compiler Engineer responsible for the ground-up development and scaling of a deep learning compiler stack for Amazon's ML accelerators (Inferentia and Trainium). The role involves architecting and implementing business-critical features, optimizing neural net models for custom hardware, and integrating with ML frameworks like PyTorch and TensorFlow.

Software Development Engineer III at Amazon Annapurna Labs, focusing on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Inferentia and Trainium). The role involves solving complex technical problems, designing and implementing innovative software solutions, and working with external and internal customers to identify adoption obstacles and opportunities in the Generative AI space.

This role is for a Sr. Machine Learning Compiler Engineer III on the AWS Neuron team, focusing on the development and scaling of a compiler for ML accelerators. The role involves architecting and implementing features for a deep learning compiler stack that optimizes neural network performance on custom AWS hardware, integrating with frameworks like PyTorch and TensorFlow. The goal is to provide significant performance improvements for large-scale ML workloads.

Senior Software Development Engineer focused on Generative AI within Amazon's Annapurna Labs, specifically working with the Neuron SDK and ML chips (Inferentia and Trainium). The role involves building and applying AI agents to improve customer adoption of these chips, optimizing software solutions for performance, durability, cost, and security, and collaborating with cross-functional teams including compiler, hardware, and ML engineers. Experience in the Generative AI space is a hard requirement.

Data Scientist role focused on developing and implementing statistical, causal, and machine learning techniques for forecasting and inventory management within Amazon's retail supply chain. The role involves creating prototypes, collaborating with software teams for production implementation, and analyzing key business metrics to influence business direction.

Senior Applied Scientist role at Amazon Advertising focused on building and deploying end-to-end machine learning models to improve traffic monetization and merchandise sales. The role involves leading ML efforts, performing hands-on analysis, driving ambiguous projects, and establishing scalable processes for model development and deployment.

Senior Manager for AI Inference Technology, leading a team to build fundamental inference technology building blocks and libraries for AWS Neuron SDK, optimizing models for Trainium and Inferentia devices. Focuses on the full development life cycle of inference libraries, enabling customers to optimize LLMs, multimodal, and generative models.

Senior Applied Scientist role at Amazon Prime Video focusing on Playback Intelligence. The role involves applying machine learning and data science to optimize video streaming quality, detect anomalies, and leverage LLMs and generative AI. Responsibilities include end-to-end ownership of product and user experience, translating business requirements into ML deliverables, defining research directions, conducting experiments, and mentoring junior scientists. The role requires experience in building ML models for business applications and designing AI solutions for real-world use cases.

Senior Software Development Engineer focused on pre-silicon hardware/software co-development for next-generation machine learning chips (like Trainium) used in AWS. The role involves working with architecture, design, and emulation teams, writing bare-metal software and ML workloads to verify chip functionality and performance.

Principal Applied Scientist role focused on applying machine learning, optimization, and economics to improve Amazon's Stores business, specifically in areas like delivery speed, seller fees, and LLM applications. The role involves leading a team, developing scientific models, benchmarks, and services, and deploying solutions in partnership with product teams.