Amazon

This role is for a Principal Solutions Architect focused on the Media, Entertainment, Games, and Sports (MEGS) vertical within AWS. The primary responsibility is to act as a strategic technical leader, driving long-term thought leadership, identifying high-value opportunities, and positioning AWS as a transformational partner for strategic customers. The role involves operating at the C-suite and VP level, advising senior technology leaders on cloud strategy and architecture, and designing scalable solutions for media, gaming, streaming, and sports workloads. A significant focus is on leveraging innovations in data patterns and AI, including Generative AI, to help customers re-imagine and transform existing systems. The role also involves evaluating new technologies, building reusable frameworks, and influencing AWS roadmaps based on customer needs. Experience with Data & AI technologies, including AI/ML and GenAI, is required, along with a strong background in cloud solutions architecture and customer-facing technical roles.

Senior Software Development Engineer role focused on developing innovative solutions in brand measurement for Amazon Ads, leveraging generative AI and machine learning to optimize advertising performance and provide AI-driven insights to advertisers.

Software Development Manager for Prime Video Personalization and Discovery team, responsible for leading engineers in designing, implementing, and delivering large technology initiatives for AI-first personalization models at scale. Focuses on product ownership, user experience, and technical strategy for recommendation systems.

Senior Applied Scientist role focused on developing state-of-the-art measurement approaches and machine learning models for Amazon's digital advertising business, operating at Petabyte scale. The role involves designing and analyzing large-scale experiments, collaborating with engineering teams to productionize models, and establishing scalable processes for model development and validation. Requires expertise in experimental statistics, machine learning, or causal inference, with a focus on building sophisticated decision engines and measurement systems.

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.

Applied Science Manager for Prime Video Personalization & Discovery, leading a team to develop and launch AI solutions for recommendation and personalization systems. Requires experience in deep learning, GenAI, RL, and recommendation systems, with a focus on end-to-end product ownership and team management.

The role focuses on improving ad selection within Amazon Ads using generative AI, LLMs, and ML optimization techniques. The primary goal is to enhance the customer shopping experience and drive revenue impact through online experimentation, ML modeling, and real-time ML solutions.

This role focuses on building and operating AWS cloud infrastructure specifically for AI training and inference workloads. The Systems Development Engineer will design, deliver, and operate server solutions that enable high performance and scalability for AI/ML and HPC. The role involves creating automation through agentic workflows and implementing AI-driven tools, impacting both AI implementation and core architecture within the AWS Hardware Engineering team.

Applied Scientist II at Amazon Prime Video focused on building and launching end-to-end AI solutions for personalization and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The role involves designing and conducting experiments to evaluate solutions and requires a strong background in machine learning model development and application.

Senior Software Development Engineer role focused on applying Automated Reasoning to verify Generative AI outputs, specifically addressing hallucinations within AWS services. The role involves designing and building new services and capabilities at scale, contributing to the evolution of the Automated Reasoning Checks (ARc) service, and making automated reasoning more accessible within AWS.

Software Development Engineer role focused on building autonomous agent systems for product lifecycle management, integrating tool use, memory, and reasoning. The role involves defining architecture and evaluation frameworks for agentic workflows, including orchestration, guardrails, and reliability mechanisms.

Senior Applied Scientist role focused on developing and deploying machine learning solutions for the gaming industry within AWS GameTech. The role involves full-stack data solutions, impacting game developers and player experiences through prediction, optimization, recommendation, and anti-cheat systems. Requires experience in building ML models, applied research, deep learning frameworks, and distributed systems, with a preference for AI product development at scale and RL/DRL experience.

Solutions Developer role focused on building prototypes and customer-facing solutions using AWS services, with a strong emphasis on Machine Learning, Agentic Design, and Generative AI. The role involves rapid development, experimentation with new technologies, and translating business problems into technical solutions.

This role focuses on applying and implementing existing ML solutions to improve global logistics and delivery experiences. The primary responsibility is to build and validate predictive models for delivery time estimation and identify delivery exceptions, directly impacting customer satisfaction and operational efficiency.

Applied Scientist III role focused on designing, developing, evaluating, and deploying data-driven models and analytical solutions for ML and NL applications. This involves applying statistical modeling, optimization, and ML techniques, building and deploying models in production, and researching novel approaches. The role also includes mentoring junior staff.

This role focuses on leveraging AI and Agentic technologies to build data products, including autonomous agents, RAG pipelines, and multi-agent orchestration frameworks. The engineer will architect and develop scalable data solutions, build ETL pipelines, statistical models, and machine learning solutions, and partner with business owners to integrate generative AI and automation into programs. The role requires deep experience in SQL, data modeling, AWS data services, and hands-on experience with LLMs, Agentic Frameworks, and RAG architectures.

Senior Software Development Engineer role focused on building and scaling agentic AI applications powered by large language models for the Amazon Shopping experience. The role involves architecting, designing, and developing back-end systems and online services, including service orchestration, agent frameworks, and real-time processing. It also includes contributing to the technical roadmap, service reliability, and optimizations for intelligent agents that reason, plan, and execute tasks. The team aims to improve search using large-scale foundation models and empower conversational applications for online shopping.

Senior Software Development Engineer role in AWS Healthcare AI, focusing on building next-generation AI solutions for healthcare providers. The role involves designing and implementing distributed systems and AI-powered healthcare solutions, leveraging generative and agentic AI to improve clinical and administrative workflows.

Software Development Engineer focused on building and scaling machine learning models for Prime Video recommendations, aiming to provide personalized content discovery for millions of customers.

This role focuses on developing and launching AI-based solutions for advertising, specifically in contextual targeting and ad syndication. The scientist will work with generative AI, computer vision, and large language models to maximize yield and deliver engaging ads. Responsibilities include partnering with Product and Engineering, driving end-to-end applied science projects, providing technical leadership, and researching new machine learning approaches.

Applied Scientist role focused on developing and implementing Generative AI solutions for Amazon's Sponsored Products and Brands advertising platform. The role involves building recommendation systems, designing new AI solutions, and driving the science vision to improve advertiser campaigns and shopper experiences. It requires end-to-end ownership from design to launch, including A/B testing and long-term strategic planning.

Software Development Engineer focused on AI for Prime Video's personalization and discovery systems. The role involves developing AI solutions using deep learning, GenAI, and reinforcement learning, leading end-to-end delivery, conducting experiments, and publishing research. It's an engineering role with a strong research component, aiming to improve customer experience for millions of users.

Software Development Engineer focused on AI for Prime Video's personalization and discovery systems. The role involves developing AI solutions using deep learning, GenAI, and reinforcement learning, leading end-to-end delivery, conducting experiments, and publishing research. It's an engineering role with a strong research component, aiming to improve customer experience for millions of users.

Software Development Engineer role focused on developing AI solutions for Prime Video's personalization and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The role involves building and guiding ML models end-to-end, leading cross-team collaboration, and conducting experiments to evaluate solutions. It also includes mentoring junior engineers and staying updated with the latest modeling techniques.

Machine Learning Software Development Engineer II for Amazon Robotics, focusing on Scanless Technologies. This role involves designing, developing, testing, and deploying software solutions that use machine learning and computer vision to automate fulfillment center operations, specifically by eliminating the need for manual scanning. The engineer will be a technical leader, solving complex problems and owning software performance, hardware integrations, and cost-optimal solutions.

Senior Software Engineer on the Velocity team at Amazon, focusing on perception and localization for autonomous robots. The role involves developing ML capabilities and infrastructure for perception/localization, optimizing algorithm performance, and building frameworks for data replay, analysis, and resource management on embedded systems.

Data Scientist role focused on designing and operating an experimentation platform for supply chain optimization. The role involves advancing causal inference methodology, building production-grade infrastructure, and developing supply chain emulation systems to evaluate policy changes. The work directly influences significant inventory investments and operational decisions, with opportunities for publication in top venues.

Data Scientist role focused on designing and operating an experimentation platform for supply chain optimization. The role involves advancing causal inference methodology, building production-grade infrastructure, and developing supply chain emulation systems to evaluate policy changes. The work directly influences significant inventory investments and operational decisions, with opportunities for publication in top venues.

Senior Software Development Engineer (SDE) on the Prime Video Personalization and Discovery team. This role focuses on building and evolving ML-driven systems for personalized recommendations and content discovery at scale for millions of Prime Video customers. The engineer will lead technical aspects, partner with stakeholders, and contribute to the strategic vision of the recommendation space.

This role focuses on developing and customizing ECAD applications for hardware engineering teams, with a significant emphasis on integrating AI/ML technologies to enable intelligent automation, design review, and design generation within traditional CAD workflows. The engineer will collaborate with AI/ML teams to integrate LLMs and machine learning capabilities, develop custom workflows, and support engineering tools.

The Sr. Technical Program Manager will lead the planning, execution, and launch of a transformation program focused on architectural transformation and infrastructure efficiency within Prime Video. This role requires a strong understanding of AI technologies, including LLMs, recommendation systems, and autonomous agents, to guide cross-functional teams in adopting and integrating AI solutions. The TPM will identify and mitigate risks associated with AI deployments, partner with leaders to align initiatives with objectives, and drive technical decisions to optimize performance and customer experience.

Senior Software Development Engineer role focused on developing advanced robotics systems at Amazon scale, integrating cutting-edge AI, control systems, and mechanical design for adaptable automation solutions. The role involves leading a team to design and implement a software framework for generalized dexterous mobile manipulation, including cloud and on-edge inferencing, real-time teleoperation, and human-machine interfaces.

Applied Scientist role at Amazon Prime Video focused on building machine learning systems for content presentation and discovery. The role involves working with multi-modal embeddings, contextualized ranking, reinforcement learning, and recommender systems to improve customer engagement with the Prime Video catalog.

Manager of Applied Science for Amazon Ads Measurement Science team, focusing on developing and leading a team to create solutions for performance measurement products. This includes leveraging Generative AI, classical ML, Causal Inference, NLP, and Computer Vision to measure ad spend impact, provide insights, and potentially develop agentic AI solutions for advertisers. The role involves managing scientists, defining strategy, and delivering scientific solutions.

Manager of Applied Science for Amazon Ads Measurement Science team, focusing on developing and leading a team to create solutions for performance measurement products. This includes leveraging Generative AI, classical ML, Causal Inference, NLP, and Computer Vision to measure ad spend impact, provide insights, and potentially develop agentic AI solutions for advertisers. The role involves managing scientists, defining strategy, and delivering scientific solutions.

Internship role focused on building AI infrastructure and ML systems, including custom silicon design, framework optimization, compiler development, and distributed training systems for AWS.

The role is for a Senior AI Innovation & GTM Programs Lead within AWS Applied AI Solutions. The primary focus is on driving organizational effectiveness by building AI-powered tools and automation using technologies like Amazon QuickSight and Kiro to streamline Go-To-Market (GTM) processes, enhance account planning, and accelerate business growth. The role involves owning the technical roadmap for AI innovation, prototyping new capabilities, and translating business needs into technical solutions.

Software Development Engineer II role focused on building and deploying machine learning models and systems for profit intelligence within Amazon. Responsibilities include production deployment, architecture design, automation of ML pipelines, and metrics design for model effectiveness. The role leverages AWS cloud services and distributed systems.

Senior Applied Scientist role focused on applying AI/ML and GenAI to credit management, B2B financial services, and payments within Amazon. The role involves developing and deploying production models for credit and fraud management, enhancing product features, and leveraging alternative data. It requires experience with foundation models, agentic frameworks, and LLM-powered automation, with a strong emphasis on operational excellence and delivering customer value through AI-driven insights and automation.

This role focuses on building and deploying ML models to detect theft, fraud, and organized crime within Amazon's global supply chain and operations. The scientist will own KPIs, automate detection, analyze operational defects, contribute to strategy, and integrate ML models into applications. The role requires a PhD or Master's with significant applied research experience in ML, particularly in fraud detection and organized crime.

This role focuses on developing and deploying machine learning and generative AI models for Amazon's Sponsored Products and Brands Ads, aiming to personalize advertising experiences and optimize the ad-serving process. It involves data analysis, model development, A/B testing, and research into new AI solutions, with a strong emphasis on productionizing these models for a large-scale consumer product.

Applied Scientist role at Amazon Advertising focusing on building full life-cycle machine learning solutions, including scaling ad performance insights through agentic systems/LLMs. The role involves hands-on analysis, modeling with large datasets, productionizing ML models with engineers, running A/B experiments, and researching innovative ML approaches to drive monetization and sales for Amazon's advertising products.

Software Development Engineer to develop a multi-modal, multi-lingual web-scale information retrieval system that combines LLMs with retrieval systems for question-answering, knowledge synthesis, and information grounding. The role involves building data pipelines, optimizing core algorithms and ranking models, designing data structures and indexing techniques, optimizing performance and scalability, integrating ML models, and developing control plane systems for the IR system infrastructure. Experience with Rust, large-scale distributed systems, and ML integration is required.

Software Development Manager for Amazon Web Services (AWS) Elastic Block Store (EBS) Capacity Engineering team. The role involves leading a team to invent and build a new capacity forecasting and planning platform using AI/ML, including machine learning models, algorithms, and agents, to automate capacity planning and purchasing for AWS data centers globally. The focus is on optimizing fleet servers, predicting demand, and balancing service, infrastructure, financial, and business constraints to support the rapid growth of AWS, especially driven by AI workloads.

Software Development Engineer III role focused on building conversational ad experiences using generative AI and LLMs for Amazon Ads. The role involves designing and developing new features, integrating AI solutions, pioneering conversational AI approaches, and creating scalable, low-latency systems. It requires strong software engineering skills and collaboration with science teams to implement LLM models in production and contribute to LLMOps.

Software Development Engineer II at Amazon focused on building advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The role involves developing a software framework for robot deployment, generalization, integration with large models and control techniques, and human-safe solutions. Key responsibilities include designing manipulation components, cloud/edge inferencing, real-time communication, and human-machine interfaces.

Software Development Engineer focused on real-time ad personalization and insights, leveraging generative AI technologies like latent diffusion models, LLMs, and RL to tailor visual ad experiences. The role involves investigating new technologies, building data pipelines, and developing platforms for ML model deployment in the Dynamic Creative Optimization (DCO) domain.

This Applied Scientist Intern role at Audible focuses on developing innovative AI solutions for recommendation, content understanding, and AI-powered product experiences. The intern will design and implement ML models, frameworks, and evaluation methodologies, enabling self-service automation and building AI systems that drive internal productivity and new product features. The role emphasizes practical implementation, collaboration with cross-functional teams, and raising AI fluency across the organization.