Amazon

The role focuses on optimizing ML kernel performance for AWS Neuron SDK on custom ML accelerators (Inferentia and Trainium). It involves designing and implementing high-performance compute kernels, analyzing and optimizing kernel-level performance, implementing compiler optimizations, and collaborating with customers and internal teams to enable and optimize ML models. The work is at the hardware-software boundary, combining deep hardware knowledge with ML expertise.

Data Scientist II role focused on applying statistical, machine learning, and GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology organization. The role involves designing, developing, and maintaining scalable models and prototypes, partnering with cross-functional teams, and creating benchmarks for GenAI model performance.

Data Scientist II role focused on applying statistical, machine learning, or GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology organization. The role involves designing, developing, and maintaining scalable models and prototypes, partnering with cross-functional teams, and communicating results to diverse audiences.

Applied Scientist role focused on developing and deploying optimization, simulation, and machine learning solutions for Amazon's Fulfillment Network. The role involves understanding operational processes, developing mathematical models, creating prototypes, partnering with engineers for production integration, and designing experiments to test solutions. The team has expertise in operations research, optimization, scheduling, planning, simulation, and machine learning.

Applied Scientist role focused on developing and optimizing delivery capacity in Amazon's Last Mile network. Requires strong skills in Operations Research or Machine Learning, building ML models, developing algorithms for business applications, and optimizing system policies. The role involves turning business requirements into mathematical models, contributing to production systems, and analyzing data.

This role focuses on designing, developing, and evaluating innovative optimization and machine learning models for Amazon's outbound transportation planning and execution systems. The scientist will work with large-scale data and distributed computing on the cloud to optimize inventory and shipments, reduce transportation costs, and improve customer experience. Collaboration with product managers and software engineers is key to building and integrating these solutions into production systems.

This role focuses on analyzing and evaluating conversational interaction data to support the training and evaluation of LLMs and machine learning models for Alexa's speech interfaces. The Language Data Scientist will own data analysis, research requests, and contribute to developing annotation workflows and evaluation conventions.

Delivery Consultant for AWS Professional Services focused on AI/ML and GenAI solutions in the Healthcare and Life Sciences sector. Responsibilities include end-to-end project implementation, designing ML pipelines and MLOps, collaborating with cross-functional teams, and advising customers on AI/ML strategies using AWS services.

This role is for a Delivery Consultant on the AWS Professional Services team, focusing on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. The consultant will work with customers to understand business needs, prepare data, develop and deploy models, and ensure solutions are scalable, secure, and performant using AWS services and MLOps best practices. The role involves acting as a trusted advisor, collaborating with cross-functional teams, and sharing knowledge.

Applied Scientist role focused on developing and optimizing delivery capacity in Amazon's Last Mile network. Requires strong skills in Operations Research or Machine Learning, building ML models, developing algorithms for business applications, and optimizing system policies. The role involves turning business requirements into mathematical models, contributing to production systems, and analyzing data.

Senior Technical Program Manager to drive organizational effectiveness through hands-on development of AI-powered tools, automation, and knowledge systems for the Field Engineering team within AWS Infrastructure Services. The role focuses on leveraging generative AI technologies, including Amazon QuickSight, to streamline processes, enhance engineering analysis, and accelerate availability solutions.

Senior Solutions Architect focused on helping GovTech ISVs build and scale generative AI and agentic systems on AWS, with a strong emphasis on regulated environments. The role involves guiding technical strategy, architecture, and productionization of AI prototypes into robust, scalable applications.

Senior Solutions Architect for GovTech ISVs, focusing on helping them build and scale generative AI and agentic systems on AWS. The role involves guiding technical strategy, architecture, and security for regulated environments, with an emphasis on modernizing platforms and ensuring AI solutions are production-ready.

Applied Scientist role focused on the intersection of AI and program analysis for a deep learning compiler stack, optimizing models for ML accelerators like Trainium. Responsibilities include designing, developing, and deploying analyzers, architecting tooling, and publishing research in compiler technology and deep learning systems software.

Software Development Engineer role focused on building applied AI solutions, specifically agentic products, within the AWS Applied AI Solutions organization. The role involves transforming research into production systems, owning end-to-end deployment of Generative AI and ML methods, and establishing scalable processes for ML development and serving.

Software Development Engineer (MLE) for the CreativeX RAPID team at Amazon, focusing on real-time ad personalization and insights. The role involves tailoring visual ad experiences using technologies like latent diffusion models, LLMs, RL, and computer vision to provide dynamically optimized creatives with low latencies. Responsibilities include investigating new generative AI technologies, prototyping, evaluating feasibility, building data pipelines, and developing platforms for ML model deployment.

Software Development Engineer role focused on building and optimizing AI-powered personalization and recommendation systems for Prime Video's Linear TV segment. The role involves designing and implementing high-performance personalization systems, productionizing ML models with Applied Scientists, architecting data pipelines, developing real-time serving infrastructure, and leading A/B testing frameworks. Requires strong software development skills, experience with ML frameworks, SQL, distributed systems, and knowledge of recommendation systems and model serving.

Senior ProServe Cloud Architect for Healthcare and Life Sciences at AWS, focusing on designing and implementing AI and cloud solutions for pharmaceutical customers. This role involves understanding customer business objectives, architecting scalable AWS solutions for clinical development challenges, and advising on emerging technologies including agentic AI applications. The position requires deep domain knowledge of the pharmaceutical sector, including data standards and compliance frameworks, and collaboration with various AWS teams to drive innovation and customer success.

Senior Delivery Consultant for AWS Professional Services, focusing on designing, implementing, and managing GenAI and ML solutions for customers. The role involves technical guidance, collaboration with stakeholders, and advising on AI/ML trends and technologies, with a strong emphasis on AWS services.

The Machine Learning Compiler Engineer II on the AWS Neuron team will support the development and scaling of a compiler for AWS Machine Learning accelerators (Inferentia and Trainium chips). This role involves architecting and implementing features for the AWS Neuron Software Development Kit (SDK), which optimizes neural network models for custom AWS hardware. The engineer will work with ML frameworks like PyTorch and TensorFlow, contributing to a toolchain aimed at improving ML performance.

Manager for an Applied Science team focused on extending Amazon Ads campaigns beyond the Amazon store using generative AI and machine learning to deliver sponsored experiences in third-party environments. The role involves leading scientists and engineers, shaping product direction, developing roadmaps, and driving advertiser outcomes through ML/GenAI solutions.

Senior Software Development Engineer role focused on building and scaling GenAI and ML solutions within the Amazon Music Catalog team. The role involves developing, deploying, and optimizing LLMs in production, working with distributed systems and data pipelines, and partnering with Applied Scientists and Product Managers to integrate AI-driven capabilities into catalog systems.

Senior Solutions Architect for GovTech ISVs, focusing on helping them build and scale generative AI and agentic systems on AWS. The role involves guiding technical strategy, architecture, and security for regulated environments, with an emphasis on modernizing platforms and ensuring AI solutions are production-ready.

Machine Learning Engineer at Amazon Ads focused on Sponsored Products and Brands, re-imagining advertising with generative AI. The role involves designing, coding, and supporting scalable ML pipelines and online serving systems, optimizing ML model performance and infrastructure, and implementing end-to-end solutions. It requires driving technical direction, building and growing teams, and collaborating on product direction. The team operates on a large product catalog with strict latency constraints and works with research scientists to deliver relevant ads.

This role focuses on building and deploying machine learning models for Amazon Devices Sales and Marketing, specifically for product recommendations, customer segmentation, and marketing initiative effectiveness. The candidate will own solutions end-to-end, from conceptualization to productionalization, and will collaborate with various teams to deliver customer-facing reporting tools and automated recommendation systems.

Software Engineer II role focused on deploying autonomous agents for supply chain optimization, leveraging generative AI and ML to build intelligent infrastructure. The role involves designing and deploying AI systems/agents, building Gen AI technologies with AWS, and collaborating with cross-functional teams.

Software Development Engineer role on the Data Center Gen AI team at AWS, focused on building generative AI solutions for data center operations. The role involves developing intelligent systems that optimize technician workflows, automate decision-making, and enhance operational efficiency using LLM integration, RAG, agent frameworks, and full-stack serverless technologies. The position aims to transform data center operations through AI/ML innovations and build platform primitives for other teams.

Partner Solutions Architect focused on Data and AI Go-To-Market (GTM) for Amazon QuickSuite, with a primary emphasis on designing and implementing enterprise BI solutions, AI-powered analytics platforms, and agentic AI systems for workplace automation. The role involves collaborating with partners and customers to adopt AWS services, devising engagement strategies, and providing architectural guidance for AI-driven business intelligence and autonomous workplace agents.

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on architecting scalable, reliable, and secure solutions, supporting the adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events.

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on providing architectural guidance, supporting the adoption of AWS services, and acting as a technical advisor to help startups build scalable, reliable, and secure solutions.

This role focuses on enabling AWS partners to build, scale, and sell Generative AI solutions, specifically Foundation Models and Agentic solutions. The Solutions Architect will develop joint solutions, create go-to-market strategies, and drive technical enablement. Key responsibilities include architecting integrated solutions, building proof-of-concepts, influencing partner roadmaps, and creating technical content. The role requires deep technical expertise in GenAI, strong partner relationship management, and the ability to act as a technical liaison.

This role focuses on applying machine learning and GenAI to develop forecasting and optimization models for Amazon's physical retail presence, supporting real estate and network planning decisions. The scientist will design, implement, and own end-to-end ML solutions, including MLOps, and enhance user interaction with GenAI. The role involves analyzing large datasets, presenting findings to leadership, and collaborating with cross-functional teams.

Software Development Engineer role focused on building and optimizing low-latency, scalable connectivity services for Alexa devices. The role involves integrating AI-driven capabilities and AI-powered features into these services, as well as leveraging AI-augmented development tools to accelerate the software development lifecycle. The team operates at a massive scale, handling billions of transactions daily, and is increasingly adopting an AI-first approach.

Senior Software Development Engineer focused on acquiring, creating, and curating high-quality software engineering datasets for training Generative AI models, including Reinforcement Learning. The role involves designing and building automated systems for data mining and quality assessment, as well as developing GenAI-powered workflow tools to streamline data collection and assurance processes.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences, aiming to improve model accuracy and reduce latency. The role involves designing and delivering software, creating infrastructure for LLMs, developing tools for evaluation, and influencing the operational roadmap for core audio services.

Software Development Engineer role focused on enhancing Alexa's audio experiences by integrating Large Language Models (LLMs), improving model accuracy, reducing latency, and building scalable API platforms. The role involves designing, implementing, and delivering software features, creating infrastructure for LLM integration, and influencing the operational excellence roadmap for audio services.

Applied Scientist role focused on developing and optimizing Visual Inertial Odometry (VIO) and sensor fusion systems for intelligent robots, involving algorithm development, embedded deployment, and leveraging ML for perception. The role requires hands-on experience with sensors, hardware, and real-world data, with a focus on real-time performance on resource-constrained robotic platforms.

This role focuses on building and evaluating state-of-the-art ML models for biology and life sciences applications, requiring experience with deep learning methods and programming in languages like Python. The role is part of a special projects team aiming to innovate at scale and bring products to market.

Software Development Manager leading a team to build AI-powered customer support products for Amazon Advertising, focusing on AI agents and automation for advertiser case resolution and campaign management.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle.

Software Development Manager for GenAI Evaluation Media (GEM) team at Amazon, focusing on visual shopping experiences. The role involves leading a team to drive technical vision and execution of AI capabilities for generating and governing billions of visual assets at scale, ensuring quality and trustworthiness for customer purchase decisions. Requires strong technical expertise, business acumen, and leadership skills to partner with stakeholders, drive innovation, and maintain operational excellence.

Senior Technical Product Manager for advanced robotics systems, focusing on AI, control systems, and mechanical design for automation at scale. Requires deep robotics engineering expertise, including motion planning, control systems, computer vision, and machine learning, with experience in ROS, real-time OS, and embedded systems. Role involves translating technical requirements into roadmaps, evaluating tradeoffs, and driving product strategy for robotic manipulation, locomotion, and human-robot interaction.

Software Development Engineer role focused on building solutions for Sponsored Products and Brands, utilizing generative AI, machine learning, and high-scale low-latency systems to improve customer experiences off the Amazon store. The role involves designing and developing components, big data systems, and ML-based approaches in collaboration with scientists and economists.

Software Development Engineer role focused on building and managing Agentic AI capabilities for AWS analytics services, specifically an Apache Spark Upgrade Agent that uses conversational interfaces and automated code transformation to reduce upgrade timelines. The role also involves managing a Model Context Protocol server for AI assistants and Agents, providing secure access to troubleshooting and code recommendation tools.

This Data Scientist II role focuses on building scientific tooling for how business customers interact with Long-Term Planning and Forecasting (LTPF) forecasts and plans. The role involves developing causal inference models, automated explainability frameworks, and variance bridging methodologies. It also includes building GenAI-powered narrative generation capabilities and automated hypothesis ranking to synthesize quantitative variance outputs into human-readable performance summaries and identify drivers of forecast error. The position emphasizes leading cross-functional programs, defining multi-year strategy, and leveraging insights for strategic decision-making.

This role focuses on developing causal inference models, automated explainability frameworks, and GenAI-powered narrative generation to translate forecasting outputs into actionable business intelligence for Amazon's business customers. The data scientist will build automated variance decomposition models and a causal model library with standardized pipelines, applying techniques from causal inference and time-series econometrics.