Amazon

Applied Scientist II at Amazon Prime Video focused on developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. The role involves end-to-end ownership of product and user experience, working with advanced approaches like foundation models to tackle cold-start problems and discover niche interests. The scientist will also publish research findings and collaborate with engineering and product teams.

Senior Applied Scientist role focused on building predictive intelligence for capacity management in AWS workspaces. This involves developing ML systems for demand forecasting, resource optimization, and cost efficiency at enterprise scale. The role requires translating business needs into production ML systems, designing algorithms, and applying advanced ML techniques like time-series forecasting, reinforcement learning, and causal inference. Emphasis on low-latency, large-scale data processing, and collaboration with product and engineering teams.

ML Compiler Engineer II on the Neuron Compiler Automated Reasoning Group, developing and maintaining tooling for fuzzers and specification synthesis for an LLVM-based compiler targeting ML accelerators (Inferentia/Trainium) for domains like Large Language and Vision. Focus on accuracy and reliability of the compiler stack.

Sr. Applied Scientist role focused on developing and implementing AI/ML solutions to improve the Amazon Selling Partner experience. This involves building scalable models, analyzing data, and staying current with LLM, RL, and agent-based AI research to translate findings into practical applications. The role requires strong ownership of the full project lifecycle and collaboration with business and engineering teams.

Senior Applied Scientist role focused on developing and productionizing AI/ML models for ad measurement and performance analysis within Amazon Ads. The role involves end-to-end solution development, leveraging Generative AI, classical ML, NLP, and Computer Vision to provide insights and automate workflows for advertisers. Responsibilities include model development, experimentation, collaboration with engineering and business teams, and mentoring junior scientists.

Applied Scientist role at Amazon Ads focusing on measurement science, developing solutions for performance measurement products, sales impact analysis, and AI tools for customer insights and workflow automation. The role involves end-to-end ownership of measurement solutions, from design to production, leveraging Generative AI, classical ML, Causal Inference, NLP, and Computer Vision.

This role bridges generative AI research and visual storytelling for Prime Video, focusing on translating ML capabilities into production workflows and understanding creative needs. The Sr. Design Technologist will assess generative models, build proof-of-concept tools, and identify gaps between model output and production requirements.

Software Development Engineer role focused on building core functionality for AWS Internet Monitoring service, leveraging Generative AI techniques for network monitoring, traffic engineering, and autonomous systems. The role involves designing, developing, and deploying AI-integrated software systems, collaborating with cross-functional teams, and ensuring operational excellence.

The Sponsored Products and Brands team at Amazon Ads is seeking an Applied Scientist to leverage generative AI and machine learning to revolutionize advertising experiences. This role involves driving end-to-end ML projects, analyzing large datasets, building and deploying models into production, and establishing scalable processes for ML development and serving. The focus is on creating innovative ad tech and shopping experiences off the store, working with external and internal partners to connect systems, understand customers, and drive results at scale, with a GenAI-first approach.

Senior Applied Scientist role focused on developing and launching AI solutions for Amazon's Sponsored Products and Brands advertising business. This involves building recommendation systems leveraging generative models, designing and implementing end-to-end AI solutions, and defining a long-term science vision. The role requires experience in building ML models, deep learning, and working with large-scale distributed systems.

Senior Software Engineer role focused on driving technical strategy and architecture for robotic software systems, including perception, navigation, motor control, reasoning, and human-robot interaction. The role involves end-to-end delivery of complex systems, leading collaboration across research and ML teams, defining technical roadmaps, and developing production-level SDKs. The team is building robots for everyday life, aiming to make robotics development more accessible and intuitive.

Manager for an AWS Applied AI Solutions team focused on building foundational systems and consumer-facing features for trustworthy AI experiences at scale within the supply chain domain. The role involves leading engineering teams, driving technical strategy for privacy-preserving and responsible AI, and developing enterprise-grade AI applications.

This role focuses on developing and scaling credit strategies for new marketplace launches within Amazon Business Payments & Lending. It involves partnering with Science teams to innovate with AI/ML for automated credit decisioning, defining product features, and managing portfolio performance. The role requires a blend of product management, data analytics, and strategic thinking to build and grow a financial services business.

Security Engineer focused on threat detection using ML and generative AI to build and improve detection capabilities at scale for Amazon's network.

Applied Science Manager to lead a team building and scaling a prompt generation pipeline for a conversational ad format powered by LLMs. The role involves developing prompt themes, quality frameworks, and driving coverage expansion, with a focus on personalization and experimentation to improve key metrics. Requires strong technical depth in NLP, LLMs, and information retrieval, along with management experience and the ability to influence product strategy.

This role focuses on developing and deploying machine learning models for Amazon's Sponsored Products and Brands Ads, aiming to improve customer experience and advertiser effectiveness. The scientist will conduct data analysis, build and optimize ML models, run A/B experiments, and collaborate with engineers to productionize solutions. They will also research new ML modeling techniques to enhance business outcomes.

The Applied Scientist will build next-generation conversational shopping experiences for Amazon Rufus, developing data-driven solutions and deploying models into production. This role involves collaboration with cross-functional teams and leveraging Amazon's data and AWS resources.

The role focuses on building ML systems with a causal modeling foundation for AWS sales optimization, designing seller incentive mechanisms, and developing intervention strategies. It involves developing rigorous causal measurement and modeling frameworks, designing programs and incentives, and building ML-based recommendation systems.

Applied Scientist role at Amazon Prime Video focusing on leveraging NLP and Computer Vision research to enhance video content understanding and customer experience. The role involves leading research direction, creating roadmaps, and developing models for business applications, with an emphasis on delivering state-of-the-art digital video experiences.

Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment using NLP and computer vision. The role involves leading research direction, developing deep learning algorithms, and potentially building agentic systems for content understanding.

This role focuses on defining and executing Go-to-Market (GTM) strategies for AWS's generative AI (GenAI) infrastructure, specifically targeting large-scale model training and inference workloads. The individual will work with key customers (Frontier AI model builders) to accelerate their adoption of AWS services, understand their infrastructure needs, and influence product roadmaps. The role involves business development, customer engagement, evangelism, and collaboration with internal AWS teams.

This role is for a Software Development Manager on the Agentic AI organization's Evaluations & Optimization team at AWS. The manager will lead a team of engineers to build systems for assessing the quality, performance, and reliability of GenAI and agentic systems, as well as optimization solutions. The work involves deep learning, distributed systems, and evaluation science, focusing on building infrastructure and tooling for evaluation workflows.

Software Development Engineer role focused on building intelligent, closed-loop decision systems for Amazon Robotics. This involves designing and building agentic AI systems that combine machine learning, real-time data processing, and LLM-driven reasoning to automate operational decision-making in robotic workflows. The role also includes developing end-to-end decision systems, scalable architectures on AWS, ML models, data pipelines, and implementing observability and evaluation frameworks. Collaboration with cross-functional teams and end-to-end ownership of production systems are key aspects.

This role focuses on strategizing and implementing AI solutions, specifically agentic AI, for enterprise clients within AWS Professional Services. The strategist will facilitate discussions, design implementation strategies, develop innovative frameworks, and collaborate with teams to create integrated AI approaches, aiming to transform consulting delivery and drive customer value through AI.

Senior Software Engineer for Amazon Robotics Autonomous Mobility team, focusing on perception and localization software for warehouse robots. Responsibilities include developing ML capabilities, sensor fusion, SLAM, and optimizing performance. Requires strong software development and leadership experience, with preferred experience in robotics ML, C++, Python, ROS, and CUDA.

Research scientist role focused on developing and launching new AI technologies for personalization in e-commerce, leveraging LLMs, recommendation systems, and information retrieval.

This role focuses on the end-to-end development and deployment of machine learning and data science solutions for intelligent communication experiences within Alexa. The Data Scientist will design, build, and improve ML models for capabilities like prioritization and intent detection, analyze large datasets, conduct experiments, and contribute to the applied science roadmap, ultimately delivering AI-driven solutions to millions of customers.

Principal Product Manager, Technical for AWS Healthcare AI, focusing on building and launching Agentic AI powered solutions for healthcare customers. The role involves defining product strategy, roadmap, GTM plans, and driving adoption and revenue for production services. Requires strong technical product management skills and business acumen within the AI/ML space.

Principal Product Manager, Technical for Alexa Connections, focusing on building AI-native communication experiences using generative AI, LLMs, real-time communications, voice, and GUIs. The role involves strategizing, driving product roadmaps, and launching 0-1 product lines, working cross-functionally with engineering, science, and design teams to deliver delightful customer experiences.

Manager of Data Science at AWS responsible for overseeing a team that builds large-scale distributed systems for abuse detection. The role involves defining business goals, aggregating data, managing research vision, mentoring scientists, and ensuring successful integration of AI models into production. Requires experience in managing data science teams, cross-functional projects, ML techniques, generative AI, foundation models, MLOps, and production deployment of AI systems.

Principal Product Manager Tech for Prime Video Personalization & Discovery, focusing on owning the vision, strategy, and roadmap for core recommendation systems and ML models. The role involves translating business problems into model requirements, defining metrics, leading A/B testing, and making trade-off decisions for ML-powered features at scale, with a strong emphasis on customer value and business outcomes.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

This role focuses on providing strategic oversight and mentorship for human-in-the-loop and model-in-the-loop data pipelines, ensuring data quality for LLM training and evaluations. The consultant will collaborate with AI teams, optimize data collection, and develop benchmarks for GenAI model performance.

Senior Software Engineer to lead a team building the operational backbone of a satellite laser communication network. The role involves architecting and delivering mission-critical tools and services for network operations, including systems that leverage machine learning and generative AI for anomaly detection, root cause analysis, and impact prediction. The engineer will also lead automation initiatives, collaborate with cross-functional teams, and mentor junior engineers.

Applied Scientist III role at Amazon Web Services focusing on the design, development, evaluation, and deployment of data-driven models and analytical solutions for ML and NL applications. Responsibilities include applying statistical modeling, optimization, and ML techniques, building and deploying models in production, and researching novel ML approaches. Requires a Master's degree in a related field and experience in programming and developing supervised/unsupervised ML models.

Manager for a team working on LLM and/or VLM post-training and alignment for new personalized shopping experiences, leveraging customer behavioral data.

The Senior Applied Scientist will build AI-based services for Amazon Q Developer, focusing on redefining developer work. This role involves building AI agents and machine learning models, working closely with software engineers to deliver end-to-end modeling solutions, and driving discussions with customers and peers on modeling approaches. The work is expected to require scientific breakthroughs in ambiguous problem areas.

This role focuses on building causal predictive models that go beyond traditional forecasting, integrating modern machine learning techniques like LLMs and computer vision to understand and predict workforce outcomes. The scientist will write production-quality code for implementation into decision-making tools, bridging causal rigor with ML innovation.

This role focuses on the end-to-end development and deployment of machine learning and data science solutions for intelligent communication experiences within Alexa. The Data Scientist will design, build, and improve ML models for capabilities like prioritization and intent detection, analyze large datasets, conduct experiments, and contribute to the applied science roadmap, ultimately delivering AI-driven solutions to millions of customers.

Product Manager for Alexa Connections, focusing on leveraging Generative AI and LLMs to build messaging experiences where Alexa acts as an agent for customers. The role involves working at the intersection of LLMs, real-time communications, voice/graphical UIs, and mixed reality to deliver delightful features.

Software Development Engineer role at Amazon Alexa Connections, focusing on integrating generative AI and machine learning into communication features to enhance customer experiences. The role involves designing and building scalable, fault-tolerant systems for AI/ML workloads, including Gen AI inference and training pipelines, within an agile environment.

Internship role for MS or PhD students in Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning. Focuses on building large-scale ML systems using large datasets and translating business requirements into prototypes. Involves analyzing and modeling terabytes of text, images, and other data.

Software Development Engineer II on the Customer Service Application Security team at Amazon. This role focuses on building innovative security solutions using Generative AI and LLMs to automate security processes, improve security posture, and increase developer productivity. The engineer will architect and develop native AWS solutions, including prompt engineering, security frameworks, and threat detection mechanisms, to create paved path solutions for developers.

This role is for a Security Engineering Manager within Amazon's AGI organization, focusing on securing Generative AI technologies. The manager will lead a team of security engineers and technical program managers to address novel security challenges like prompt injection, model poisoning, and data leakage. Key responsibilities include setting strategic direction for GenAI security processes, influencing stakeholders, developing team culture, and driving the adoption of GenAI-specific security practices and tooling. The role requires staying current with emerging GenAI security threats and mentoring team members.

Software Development Engineer role focused on designing, developing, and deploying full-stack robotic planning, tracking, and workcell solutions using AWS and AI-driven sortation optimization. The role involves building software for sortation at scale, improving safety, and optimizing package flow and fleet orchestration through ML-powered algorithms and intelligent systems.

Software Development Engineer role focused on building and operating the data platform infrastructure for an AI-driven analytics platform at AWS Identity. This involves designing and managing ingestion, transformation, and serving pipelines for petabyte-scale data to feed ML models and LLM agents. The role also includes productionizing ML models, building feature engineering infrastructure, and ensuring platform resilience and scalability.

This role leads strategic programs for Amazon Ads' AI infrastructure core services that accelerate agentic AI development. The TPM will define and execute the agentic AI core infra product roadmap, drive agent builder adoption, and ensure the core services scale to support multi-agent workflows and production-grade reliability for advertiser-facing and internal agents.

Manager for an Applied Scientist team focused on optimizing the returns and re-commerce process using ML, NLP, and Information Retrieval. The role involves managing scientists and engineers, developing ML models for business applications, and building scalable software systems.