Amazon

Senior Solutions Architect for AWS, focusing on Agentic AI and AI-assisted software development for a major European telecommunications group. The role involves owning the end-to-end technical relationship, designing scalable and secure architectures, and influencing strategic technology decisions at CxO/VP level, while navigating complex sovereignty and compliance requirements.

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.

This role focuses on evaluating AI systems, specifically LLMs, by designing and executing benchmarking and audit activities. The core responsibilities include assessing model quality, compliance, robustness, and fairness, as well as handling annotations for training and measuring AI models. The role also involves preparing audit reports and ensuring data quality.

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.

Applied Scientist role focused on building GenAI-powered data solutions, agentic systems for quality issue detection, and ranking/recommendation models for e-commerce. The role involves designing, developing, testing, and deploying scalable ML solutions, working with state-of-the-art models like LLMs and image-to-text.

This role focuses on implementing and building ML/LLM solutions for business needs, collaborating with scientists, writing code, and optimizing solutions. It involves product pilots and developing technical documentation.

This role focuses on implementing and scaling Generative AI solutions for AWS customers, acting as a consultant to design, train, fine-tune, and deploy bespoke AI applications. It involves working with customers to identify use cases, navigate technical challenges, and ensure responsible and cost-efficient AI implementation.

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.

The AI Benchmarking Lead will focus on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. This role involves benchmarking AI models, evaluating audit processes, improving audit consistency, and enforcing quality standards to support the scaling of the product to a wider seller base.

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 focuses on designing, developing, and deploying full-stack applications and data-intensive systems for supply chain optimization and automation. It involves building scalable backend services, frontend applications, data pipelines, and implementing end-to-end machine learning solutions within the Amazon production environment to improve supply chain forecasting and automation.

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 II focused on building AI-powered solutions using LLMs to transform Amazon's Seller Support experience by developing scalable services for a next-generation support platform.

This role focuses on guiding enterprise customers in adopting and scaling GenAI/ML and Agentic technologies on AWS. The Specialist Solutions Architect will act as a trusted advisor, designing technical architectures, providing recommendations on various aspects of cloud services, and influencing the roadmap of AWS GenAI/ML and Agentic features. The role involves creating and sharing best practices, technical content, and reference architectures, as well as evangelizing AWS technology through various channels.

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.

Software Development Engineer focused on building and scaling real-time agentic AI systems for Alexa's communication features, involving design, architecture, and full-stack development.

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.

Software Development Engineer role focused on building agentic APIs and integrating advanced AI technologies (Generative, Agentic, Real-time AI) into Alexa's communication features. The role involves influencing product strategy, optimizing for low latency and scalability, and ensuring high-quality software delivery within an Agile environment.

Senior Software Development Engineer role focused on building agentic APIs and cloud services for Alexa Connections, leveraging Generative, Agentic, and Real-time AI to enhance conversational experiences. The role involves influencing product strategy, optimizing software for performance, and leading integration of AI systems.

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.

Manage a team of engineers building ML and generative AI systems for retail operations automation, focusing on catalog management, supply chain, and operational efficiency. The role involves architectural decisions, mentoring, and cross-team coordination to deliver scalable, reusable platforms.

The role is for a Senior Manager of Software Development focused on building next-generation Agentic security systems at Amazon. The position involves leading teams to create AI-powered security products from the ground up, working at the intersection of AI and security at a large scale. The manager will collaborate with security, engineering, and science leaders, and shape products that transform business security practices.

Applied Scientist role focused on building machine learning models for Amazon Search, developing new ranking features, and improving the ML framework for training and offline evaluation. The role involves designing, developing, and implementing production-level code for billions of search requests, with an emphasis on low-latency predictions and high throughput 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.

Software Development Engineer role focused on building and deploying computer vision and machine learning systems for Amazon's global fulfillment network. The role involves end-to-end ownership of systems that provide vision-based insights for item identification, defect detection, and decision-making in manual and robotic operations, supporting downstream business processes and flagship devices.

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.

AWS Solutions Architect role focused on prototyping with Agentic AI, Machine Learning, Deep Learning, Generative IA, IoT, and Serverless Architectures. The role involves architecting and developing solutions to demonstrate the art of the possible to customers, with a focus on rapid, time-boxed prototyping engagements.

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.

Applied Scientist role focused on building machine learning and optimization models for Amazon's large-scale transportation planning systems, including dynamic pricing and network planning. The role involves designing, building, and implementing scalable products and algorithms within production systems, with a focus on external freight and marketplace operations.

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.

Senior Delivery Consultant (GenAI FullStack SDE) at AWS Professional Services, focusing on building end-to-end Generative AI applications for enterprise customers. The role involves full-stack development, designing and implementing AI agent architectures, and leveraging AI-powered development tools. The primary focus is on delivering solutions using AWS services, with a secondary emphasis on the underlying inference infrastructure.