Amazon

This role focuses on developing and deploying advanced ML/AI technologies for Amazon's catalog expansion, involving information extraction, web crawling, and comprehension using deep learning, NLP, and image processing. The scientist will build scalable systems to extract and structure information from the web, including visually rich documents, and work with LLMs/SLMs and agentic systems. The role requires a strong foundation in ML model development, deployment, and collaboration with software engineering teams.

Applied Scientist II at Amazon Fulfillment Technology (AFT) Science, focusing on developing production solutions for Amazon's Fulfillment Network using operations research, optimization, statistics, machine learning, and GenAI/LLM. The role involves designing, building, and deploying scalable mathematical models and optimization-driven solutions to improve process efficiency and associate experience within the fulfillment network. Collaboration with scientists, software engineers, and product managers is key, with a focus on translating research into production systems.

Senior Manager role focused on leading AI/ML innovation for network planning solutions, involving demand forecasting and network optimization algorithms. The role requires developing and deploying production-ready models, architecting scalable AI/ML infrastructure, and driving scientific innovation from research to production, ultimately translating AI/ML capabilities into measurable business outcomes. It emphasizes leading a team of applied scientists and collaborating with cross-functional partners.

Machine Learning Engineer II on an Amazon Special Projects team focused on creating new products and services using Generative AI and LLMs. Responsibilities include developing and maintaining platforms for LLM development, evaluation, and deployment, processing large datasets, scaling models, and optimizing performance. Experience with distributed model training is required.

Senior Software Engineer role focused on architecting and building next-generation robotic systems for warehouse automation. The role involves designing motion planning algorithms, developing vision-guided manipulation systems, and orchestrating complex multi-step workflows using behavior trees or state machines. Experience with robotics middleware (ROS/ROS2) and ML frameworks is preferred.

This role focuses on designing and implementing generative AI solutions for enterprise customers in Mexico, leveraging AWS technologies. The Senior Generative AI Solutions Architect will guide customers on AI architecture, security, data governance, and operational best practices, while also creating technical artifacts, workshops, and content. Key responsibilities include architecting solutions for multi-agent orchestration, RAG, and chat-based assistants, and helping customers navigate regulatory frameworks and achieve production readiness.

This role focuses on enabling Private Equity (PE) firms and their portfolio companies to leverage Generative AI and Machine Learning to solve business challenges. The Solutions Architect will design and architect end-to-end AI/ML solutions, including AI agents and RAG applications, using AWS AI services. The role involves partnering with PE firms, understanding business requirements, and guiding customers in architecting enterprise-grade GenAI solutions.

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models at scale. The individual will act as a trusted advisor, architecting solutions, supporting adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events.

The Sr. Applied Scientist will focus on developing and implementing machine learning models and algorithms to optimize Amazon's Last Mile logistics operations. This role involves analyzing business challenges, creating metrics, developing scalable processes and tools, and working with technology teams to improve delivery efficiency and cost-effectiveness. The position requires a PhD in a quantitative field and significant experience in building ML models for business applications.

Senior Applied Scientist role focused on using ML/AI to understand demand-side signals in e-commerce, empower sellers to grow their business, and improve customer experience. Responsibilities include developing scalable seller-facing solutions, analyzing business data, designing and evaluating innovative models, and collaborating with engineering teams for real-time implementation.

Applied Scientist role at Amazon Ads focusing on Generative AI, AI Agents, and large-scale ML for demand forecasting. Responsibilities include leading ML initiatives, developing and optimizing forecasting models, building and deploying ML models, designing A/B experiments, establishing scalable ML infrastructure, and researching innovative ML techniques. Requires 3+ years of model building experience, a PhD or Master's with 4+ years of experience in a related field, and programming experience in Java, C++, or Python. Preferred qualifications include experience with experimental design and deep learning frameworks.

The Sr. Software Development Manager will lead a team of compiler engineers developing, deploying, and scaling a compiler targeting AWS Inferentia and Trainium ML accelerators. This role involves deep knowledge of resource management, scheduling, code generation, and optimization for new instruction architectures, with a focus on delivering high-performance, low-cost ML inference and training solutions for AWS customers.

The role focuses on applying advanced analytical, statistical, and machine learning techniques to improve Amazon's Selling Partner experience through a Generative AI-powered conversational assistant. Responsibilities include analyzing seller pain points, evaluating feature performance, designing measurement frameworks (A/B testing, causal inference), applying NLP and statistical modeling to unstructured data, and partnering with cross-functional teams to influence product roadmaps. The goal is to enhance the Selling Assistant by responding to seller feedback and implementing fixes in the GenAI solution.

The Sr. Applied Scientist Pricing Optimization role at Amazon Leo focuses on building foundational ML models to optimize pricing and product feature strategies for a satellite broadband network. This involves predicting customer behavior, modeling multi-product bundling, and implementing scalable inference systems.

Software Engineer focused on performance optimization for distributed training of large-scale AI/ML models (LLMs, multi-modal) on AWS Neuron accelerators. This involves tuning across the software stack, including collective communications, memory utilization, compiler optimizations, and kernel performance, working with PyTorch and JAX.

Seeking a Software Engineering Manager to lead a team developing compiler optimization algorithms and deploying a new compiler for AWS custom hardware (Inferentia and Trainium chips). The role involves technical leadership, mentoring, and partnering with AWS ML services teams to improve deep learning model performance and productivity.

Software Development Engineer 2 role on the Unified Risk Evaluation System team at Amazon Business, focusing on fraud prevention and risk management using machine learning and scalable systems to process billions of transactions globally. The team builds self-service capabilities for ML model experimentation and manages numerous risk use cases.

The role focuses on optimizing the performance of machine learning kernels for AWS's custom ML accelerators (Inferentia and Trainium) by developing and implementing high-performance compute kernels, optimizing compiler optimizations, and analyzing kernel-level performance. This involves working at the hardware-software boundary to ensure optimal performance for deep learning and GenAI workloads.

Software Development Engineer II role focused on building and maintaining data services for training, evaluating, and benchmarking Gen-AI models. This involves Human-In-The-Loop (HIL) data labeling for Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF), as well as supporting evaluations and active learning. The role contributes to powering AWS Nova and Alexa features.

Senior Software Engineer to lead the design and evolution of AI-driven systems for generating, selecting, and optimizing marketing and merchandising assets at scale across Amazon worldwide. The role involves building systems that automatically produce and adapt images, text, and multimodal content, balancing creative flexibility, brand constraints, and performance. It requires end-to-end ownership across model integration, distributed services, and measurement frameworks, with a focus on architectural leadership and mentoring.

Lead ML teams building large-scale forecasting and optimization systems for Amazon's global transportation network, impacting customer experience and cost. The role involves setting scientific direction, mentoring scientists, and delivering production-grade ML solutions at scale, using techniques like deep learning and reinforcement learning.

Data Scientist II at Amazon Private Brands focused on applying Generative AI, Machine Learning, Statistics, and Economics to product assortment, business decisions, and product inputs. The role involves investigating business problems, inventing novel solutions, prototyping, and deploying production software, with research areas including NER, product substitutes, pricing optimization, agentic AI, and LLMs. The Data Scientist will also guide other scientists and publish research.

This role focuses on prompt engineering for Generative AI and LLMs, involving the full prompt lifecycle from concept to production. Responsibilities include developing Python code, managing CI/CD pipelines, architecting contextual frameworks, and testing prompts to enhance AI performance and address real-world challenges like counterfeit detection within the Trustworthy Shopping Experience team.

Software Development Engineer III role at Amazon, focused on building and optimizing the core components of the Amazon Quick Suite, an AI-powered assistant for enterprise productivity. The role involves leveraging generative AI to transform how businesses operate by answering questions, providing summaries, generating content, and completing tasks securely based on enterprise data, with a strong emphasis on unifying disparate data sources through secure connectors.

Software Development Engineer II at Amazon's Annapurna Labs, focusing on distributed AI/ML systems and collective operations for scaling AI across multiple accelerators and servers. The role requires strong C/C++ and Linux skills, with experience in embedded systems, high-speed networking, or HPC interconnects being valuable. This position is on the forefront of AI/ML, working with large-scale clusters and models within AWS's EC2 infrastructure.

The Language Engineer will develop diverse datasets for training and evaluating Amazon AI models, using synthetic data generation, model-supported generation, and human-in-the-loop methods. This role involves designing data collections, analyzing data, building tools for data creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with speech, text, and multimodal data is required.

Software Development Engineer on the Ring AI Team, focusing on cloud services for machine learning operation pipelines that handle large-scale data and enable rapid model optimization by data scientists. The role involves working with cloud services, distributed systems, and web services to deliver a world-class platform for fast-paced AI model development.

Software Development Engineer on the Ring AI Team, focusing on cloud services for machine learning operation pipelines that handle large-scale data and enable rapid model optimization by data scientists. The role involves working with cloud services, distributed systems, and web services to deliver a world-class platform for fast-paced AI model development.

This role focuses on providing domain expertise to human-in-the-loop and model-in-the-loop data pipelines for LLM training and evaluations. The Senior Domain Expert Lead will ensure data quality, optimize data collection, and mentor junior team members, while staying updated on GenAI applications in their domain.

Senior Applied Scientist role focused on developing next-generation advanced robotics systems that combine AI, control systems, and mechanical design for automation at Amazon's scale. The role involves research and implementation of deep learning and LLMs for robotics, with a focus on simulation, physics-based modeling, and sim-to-real gap reduction.

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.

Applied Scientist role focused on developing and implementing forecasting and optimization models using ML and GenAI to support real estate and store planning decisions for Amazon's grocery business. The role involves analyzing large datasets, building end-to-end solutions, and collaborating with cross-functional teams to drive adoption of insights and models.

Software Development Engineer role focused on building a new Generative AI application (QuickSuite) for enterprises within AWS. The role involves translating requirements into deliverables, prototyping, designing, developing, and deploying scalable services, and mentoring junior engineers. It's an early-stage initiative with a focus on solving complex technical challenges in AI.

Research Engineer on the AWS Agentic AI team building a new Generative AI application called QuickSuite for enterprises. The role focuses on defining, designing, and leading the development of tools to accelerate science experimentation and the delivery process, bridging the gap between science and engineering for faster production.

Senior Software Development Engineer to build a new Generative AI application (QuickSuite) for enterprises, focusing on developing scalable and reliable distributed services. The role involves translating requirements into deliverables, prototyping, and mentoring other engineers.

Software Development Engineer role focused on building internal tools and external solutions for 3P Sellers using generative and agentic AI. The role involves working with product managers and other engineering teams to create and execute a roadmap of user experiences, incorporating the latest developments in generative AI to deliver agentic AI solutions.

This role focuses on building and deploying reliable, scalable, and high-performance ML/AI solutions, leveraging Big Data, AppDev, or DevOps experience. It involves working closely with Data Scientists and Data Engineers to deliver end-to-end solutions, utilizing ML frameworks, algorithms, and ML pipelines, with a strong emphasis on hosting and deployment of models.

Software Development Manager for AWS Neuron Tools team, responsible for leading engineers to develop and maintain high-performance monitoring and profiling tools for AI accelerators (Inferentia, Trainium). The role involves managing the full development lifecycle of the Neuron Profiler, ensuring scalability, reliability, and usability, and collaborating with cross-functional teams to optimize AI workloads. Experience with ML-specific profiler tools and performance analysis is required.

Senior Data Scientist role focused on developing and deploying machine learning models and AI agents for logistics optimization, fraud detection, and revenue management. The role involves end-to-end model development, from data analysis to production deployment and monitoring, with a focus on agentic AI systems and ML-powered fraud detection.

Senior Data Scientist/BI Engineer at Amazon FBA EU Analytics to own high-impact BI, science, and AI initiatives. Develop and deploy scalable AI solutions including machine learning models, causal inference, and optimization algorithms to improve seller experience, ensure compliance, and optimize fulfillment economics. Partner with Product, Tech, Operations, Finance, and Legal/Compliance to translate business problems into scientific questions and productionized solutions. Leverage Generative AI and LLMs for various use cases. Drive experimentation and decision science at scale, and mentor other scientists.

Data Scientist for Prime Air focusing on applied ML and experimentation to improve customer journey, drive expansion, and optimize delivery operations. The role involves developing statistical and ML techniques, building predictive models, designing experiments, and presenting findings to leadership, with a focus on shipping models that have a direct business impact.

Applied Scientist II at Amazon Shipping focused on building production-quality ML models for transportation logistics. This role involves improving package movement planning and execution by addressing challenges in cost auditing, financial data quality, delivery delay prediction, and first-mile shipping cost reduction. The scientist will utilize various ML paradigms, ensure scalability across regions, and contribute to the ML community through publications and mentorship.

The Language Engineer II role focuses on improving Alexa Shopping features by generating high-quality data, running experiments, and prompt engineering Large Language Models for API delivery. This involves analyzing and automating processes for collecting and annotating LLM inputs/outputs, applying Generative AI techniques, and optimizing data representation of human language. The role collaborates with scientists, engineers, and program managers to enhance the voice shopping experience and owns customer-facing ML models for specific features.

Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior.

Manager, Software Development for Alexa AI in India, focusing on speech and language solutions. The role involves leading a team to pioneer ML tools and processes, build scalable applications, and contribute to system architecture and technical vision for Alexa AI.

Senior Software Development Manager for Kiro, an intelligent development environment focused on Agentic AI systems. The role involves leading engineering teams to build innovative AI products from the ground up, partnering with ML science teams, and working at the intersection of AI and cloud services. The focus is on building foundational AI services and agentic systems for enterprise customers.

Manager for an Applied Science team focused on developing and deploying machine learning and optimization solutions for Amazon's publisher monetization platform. The role involves leading science and engineering teams, defining technical roadmaps, and collaborating with stakeholders to drive business impact at scale.

Applied Scientist role focused on building and deploying end-to-end machine learning solutions to prevent eCommerce fraud and manage transaction safety within Amazon's production environment. The role involves innovating with GenAI/LLM/VLM technologies, analyzing large datasets, and creating automated risk evaluation and operational systems.