Careers

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Engineer II Job Location: Westborough, Massachusetts Job Number: AMZ9624441 Position Responsibilities: Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics. Implement data structures using best practices in data modeling, ETL/ELT processes, SQL, Oracle, and OLAP technologies. Provide on-line reporting and analysis using OBIEE business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture. Analyze source data systems and drive best practices in source teams. Participate in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance. Produce comprehensive, usable dataset documentation and metadata. Evaluate and make decisions around dataset implementations designed and proposed by peer data engineers. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior data engineers. Position Requirements: Master's degree or foreign equivalent degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field and one year of experience in the job offered, or as an Operations Research Analyst, Database Developer, or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and one year of experience. Must have one year of experience in the following skill(s): (1) developing and operating large-scale data structures for business intelligence analytics using each of the following: (i.) ETL/ELT processes; (ii.) OLAP technologies; (iii.) data modeling; (iv.) SQL; and (v.) Oracle. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $142,064/year to $178,800/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of innovative AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems. You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll develop breakthrough foundation models that enable robots to perceive, understand, and interact with the physical world in unprecedented ways—with a strong emphasis on the hardware systems that bring these models to life. You'll drive independent research initiatives in areas such as locomotion, manipulation, motor control, actuator design, sim2real transfer, and multi-modal robot learning, designing novel frameworks that bridge state-of-the-art research with real-world hardware deployment at Amazon scale. In this role, you'll balance innovative technical exploration with hands-on hardware implementation, collaborating with mechanical, electrical, and controls engineering teams to ensure your models and algorithms perform robustly on physical robotic platforms in dynamic real-world environments. You'll have access to Amazon's computational resources and advanced robotics infrastructure—including high degree-of-freedom prototype platforms, custom actuators, and precision sensing systems—enabling you to tackle ambitious problems in areas like multi-modal robotic foundation models, motor-level control optimization, and efficient model architectures that scale across diverse robotic hardware. Key job responsibilities - Drive independent research initiatives across the full robotics stack, including robot co-design, manipulation mechanisms, innovative actuation and motor control strategies, state estimation, low-level control, system identification, reinforcement learning, and sim-to-real transfer, as well as foundation models for perception and manipulation - Lead full-stack robotics projects from conceptualization through hardware deployment, taking a system-level approach that integrates actuator dynamics, sensor feedback (force/torque, IMUs, encoders), and electromechanical constraints with algorithmic development - Develop and optimize control algorithms and sensing pipelines for physical robotic hardware, including motor characterization, actuator performance tuning, and robust sensor integration in production environments - Collaborate with hardware, mechanical, and electrical engineering teams to ensure seamless integration of learned models across the robotics stack—from embedded compute and communication buses to actuator-level control - Contribute to the team's technical strategy and help shape our approach to next-generation hardware-aware robotics challenges, including hardware-in-the-loop validation and prototype-to-deployment transitions A day in the life - Design and implement innovative systems and algorithms, leveraging our extensive computational and robotics hardware infrastructure to prototype and evaluate at scale - Collaborate with hardware and software engineers to solve complex technical challenges spanning motors, actuators, sensors, and learned control - Lead technical initiatives from conception to hardware deployment, working closely with robotics engineers and lab teams to integrate your solutions into physical robotic platforms - Participate in technical discussions and design reviews with team leaders, hardware engineers, and fellow scientists - Leverage our compute cluster and advanced robotics lab—including high-DoF prototype platforms and custom actuation systems—to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that perform reliably on real-world robotic hardware About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). Key job responsibilities Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision. We are also looking for talents with experiences/expertise in building large-scale, high-performing systems. A day in the life 0

Amazon's Selling Partner Support handles tens of millions of contacts annually worldwide. The Titans Science team is transforming this experience by building AI agents that autonomously resolve seller issues, learn from every interaction, and continuously improve with minimal human intervention. These agents reason, remember, and adapt — from understanding the seller's context and selecting the right solution, to routing contacts optimally, automating resolution end-to-end, and augmenting associates with AI when human judgment is needed. We do this in deep partnership with multiple engineering and product partners. We are looking for a Senior Applied Scientist who wants to work at the intersection of reinforcement learning, agentic architectures, and large-scale production systems. You will be directly connected to the problems sellers face every day, translating real customer pain into science solutions that operate at massive scale. You will frame ambiguous business challenges as tractable ML problems to shipping systems that measurably improve millions of seller interactions. Key job responsibilities - Own end-to-end research and development of RL-based agent improvement systems — from problem formulation through production deployment and impact measurement. - Design novel approaches to preference learning, reward modeling, and policy optimization in the context of conversational agents operating over real-world tools and APIs. - Build and maintain evaluation frameworks that measure agent quality across multiple dimensions: helpfulness, correctness, safety, and alignment with operational standards. - Collaborate with a team of scientists that work on forefront of Natural Language Understanding, Optimization, Machine Learning and Statistics - Partner with 10+ engineering teams to deploy models into production systems serving sellers worldwide. - Publish research at top venues (NeurIPS, ICML, EMNLP, AMLC) — the complexity of our problems produces publishable work, and we actively support it. - Raise the scientific bar through rigorous peer review, mentorship of junior scientists, and contribution to hiring. A day in the life You read the latest research papers and implement novel techniques by building rapid prototypes using AI-assisted coding tools, then taking what works from prototype to production. You collaborate closely with product managers and engineering teams to translate seller pain points into deployed science solutions. You influence leadership by bringing the state of the art to strategic decisions about where the organization invests, and you drive the science roadmap for your domain — identifying new research directions, proposing experiments, and making the case for what to build next. You mentor other scientists on the team, raising the bar on rigor and execution and get mentored by Principals across the org. Finally, you attend meetings with other Amazonians to stay connected to the seller experience by understanding the real problems sellers face so your models solve what actually matters. About the team Titans Science is a growing team of scientists building the AI that powers Amazon's seller support experience. We operate in across capabilities such as Agentic Systems, Knowledge Retrieval & Query Understanding, and Content Intelligence & Automation, each owning distinct problem spaces but sharing evaluation infrastructure and research insights. We work backwards from business problems, deeply understanding the problem space and domain, defining gold-standard datasets, success metrics, and guardrails. This lets us run parallel experiments, compare approaches rigorously, and ship the best Science models to production. We publish at internal conferences and external venues, and we actively invest in research that compounds over multiple product cycles. The team sits in Seattle and operates with high autonomy. Scientists own their domains end-to-end, from problem framing through production deployment. We value speed over perfection, scientific rigor over polish, and experimentation over debate. We value diverse experiences. Even if you do not meet all of the preferred qualifications listed above, we encourage you to apply. The team fosters an inclusive learning culture where individual growth is a priority — you will find mentorship, knowledge-sharing, and career-advancing resources here.

Amazon Ads Brand Safety & Suitability protects advertisers from exposure to unsafe, unsuitable, or policy-violating content across web, mobile app, CTV, and audio advertising inventory. Our mission is to ensure that every ad impression delivered through Amazon's demand-side platform appears adjacent to content that meets advertiser trust expectations while giving brands granular controls to define suitability on their own terms. We operate at the intersection of advertiser trust, publisher quality, and supply integrity. AI is fundamentally changing the content landscape. Content is now generated at unprecedented scale — faster, cheaper, and increasingly sophisticated. Low-quality, deceptive, AI-generated, and synthetic content evolves in real time, constantly adapting to evade detection. The volume and velocity of new content entering the advertising system has outpaced traditional classification approaches. We are looking for an Applied Science Manager to lead the next generation of AI-powered Brand Safety and Content Classification systems designed to protect advertisers and elevate supply quality at internet scale. This is not a traditional classification problem. Your team will build systems that make millisecond-level decisions across billions of content signals while continuously adapting to emerging content risks driven by generative AI. You will own the science roadmap for LLM-powered classification and semantic understanding, real-time multimodal content evaluation, adversarial ML and adaptive model resilience, proactive risk intelligence and content risk hunting, AI-generated and synthetic content detection, and large-scale abusive content system identification and disruption. You will define how modern AI separates high-quality advertising inventory from unsafe, unsuitable, and policy-violating content — across web, mobile app, CTV, and audio surfaces. What Makes This Role Unique Generative AI has dramatically lowered the cost of producing deceptive, policy-evasive content, and the adversary evolves daily. Your detection systems must reason contextually, adapt rapidly, and generalize beyond previously seen content risk patterns. Static models fail here; you will build living systems that learn and respond in real time. You will do this at internet scale, developing low-latency ML and LLM-powered systems evaluating content safety, brand suitability, misinformation risk, and emerging content risk vectors across massive real-time traffic streams, making billions of decisions per day with single-digit millisecond latency constraints. This role sits at the intersection of frontier AI research and large-scale production engineering, combining deep science, system-wide impact, and business-critical outcomes. The models your team ships directly influence billions of dollars in advertising spend and the trust of the world's largest brands in Amazon DSP. The Science Problems Are Genuinely Hard You will tackle challenges including detecting sophisticated AI-generated and synthetic content, understanding nuanced contextual brand risk, identifying coordinated MFA space before they scale, balancing precision, recall, latency, explainability, and fairness, designing adaptive models resilient to adversarial evolution, and leveraging LLMs for semantic understanding in real-time, latency-constrained environments. Why This Matters Few roles offer the opportunity to work at the intersection of frontier AI, internet-scale production systems, adversarial environments, and business-critical impact — while tackling open-ended scientific challenges with real-world societal relevance. As AI reshapes the internet, the systems your team builds will define what trustworthy, high-quality digital systems look like for the next decade. Key job responsibilities 1. Vision, Strategy & Roadmap a) Develop the vision, charter, and long-term strategy for Applied Science solutions that enhance critical parts of the contextual ads product. b) Drive the strategy and technical roadmap for LLM and ML-based classification systems. c) Keep updated on the industry landscape in contextual advertising and identify algorithm investments to achieve industry-leading solutions. 2. Team Leadership & Talent Development a) Lead a cross-functional team of Applied Scientists and SDEs; grow a high-performing Applied Science team focused on Brand Safety and AI-driven risk intelligence. b) Hire, develop, and mentor senior scientists; accelerate the pace of innovation in the group. c)Build a culture of innovation, scientific rigor, velocity, and long-term thinking. 3. Technical Execution & Delivery a) Drive end-to-end delivery — from research and experimentation through production deployment at billions of classifications per day. b) Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation. c) Use machine learning and statistical techniques to create new, scalable solutions. 4. Innovation & Frontier Research a) Push the boundaries of multimodal understanding, semantic reasoning, and adaptive learning systems. b) Build proactive detection and risk-hunting capabilities for emerging abuse trends. c) Continuously learn about new developments in ML and AI; identify how these can be rolled into building industry-leading solutions for Amazon Advertising. 5. Organizational Influence & Cross-Functional Partnership a) Influence org-wide GenAI strategy; represent the team's technical direction to senior leadership. b) Partner closely with Product, Policy, Ads Quality, and Infrastructure teams to operationalize AI at scale. c) Work proactively with engineering teams and product managers to evangelize new algorithms and drive implementation of large-scale complex ML models in production. 6. Business Impact & Thought Leadership a) Drive core business analytics and data science explorations to inform key business decisions and algorithm roadmap. b) Showcase innovation via peer-reviewed publications and whitepapers.

Join Amazon's Last Mile Technology Revolution! Are you ready to reshape the future of logistics? Join us in transforming how millions of packages reach their final destination through state-of-the-art technology and innovation! The Last Mile Technology organization is pioneering advanced solutions that are revolutionizing Amazon Logistics (AMZL). Our mission is to create intelligent, efficient, and scalable systems that will transform the delivery experience. We're building the future of last-mile logistics while maintaining Amazon's highest standards for safety and reliability. The Last Mile challenge is a fascinating blend of real-world complexity and technological innovation. We're tackling multidimensional problems that involve enabling AI agents to perceive and navigate complex delivery environments, understanding dynamic scenes through visual data, and adapting to everything from unexpected obstacles to varying weather and lighting conditions – all while ensuring every package arrives safely as per our promise. As an Applied Scientist on our Last Mile Technology team, you'll be at the forefront of developing computer vision and perception systems that enable us to understand and interact with the physical world. You'll design and implement deep learning models for visual perception, build algorithms that enable decision-making, and create robust systems that allow AI agents to operate safely across diverse geographical areas. Your research must excel in environments ranging from dense urban centers to suburban neighborhoods, each presenting unique visual and navigational challenges that require innovative solutions in perception and control. What Makes This Role Exciting: Real-World Impact: Your computer vision models and control algorithms will power AI agents that deliver millions of packages to customers, making their lives better every day Scale That Matters: Develop perception systems that operate across thousands of delivery agents in different cities, weather conditions, lighting scenarios, and dynamic environments Innovation at Scale: Publish novel research and create entirely new approaches to visual perception, scene understanding, and control systems End-to-End Science: Work on complete solutions from object detection and tracking to path planning and control, from sim-to-real transfer to real-world deployment and continuous learning from agent experiences

The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist specializing in the design of microwave components for use in cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for Amazon quantum processors. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of Amazon quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for Amazon reach commercial viability in quantum computing . A day in the life As you research, design, and implement cryogenic microwave signal conditioning solutions, you will also: Participate in requirements, design, and test reviews. Work cross-functionally to help drive decisions using your unique technical background and skill set. Define and maintain standards for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly.

At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale. As a Senior Research Engineer embedded in our science team, you'll be instrumental in transforming innovative research into high-performance production systems. You'll collaborate directly with scientists to build and optimize large-scale transformer models for robotics applications. In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up. You'll leverage PyTorch and NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications. Key job responsibilities - Design, implement, and optimize distributed training systems that scale across thousands of GPUs and nodes for large-scale training workloads. - Develop high-performance optimizations to maximize throughput and efficiency. - Develop reusable frameworks and libraries to improve training reproducibility, reliability, and scalability for new model architectures. - Establish standards for reliability, maintainability, and security, ensuring systems are robust under rapid iteration. - Collaborate with researchers to influence model architectures for optimal hardware utilization - Develop comprehensive benchmarking frameworks to measure and optimize model performance A day in the life In this role, you will: - Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques - Partner with scientists to analyze model architectures and propose efficiency improvements - Implement and benchmark various optimization strategies for large-scale models - Debug performance bottlenecks using NVIDIA profiling tools - Participate in technical discussions about new model architectures with the science team - Manage pre/post training runs and continue improve system stability and throughput - Prototype new acceleration approaches using emerging compilation frameworks

The NASC & TOM Science team owns Operations Research, Machine Learning, and AI projects across the North America Sort Center (NASC) and Transportation Operations Management (TOM) planning and operations organizations. We turn complex network, labor, and capacity problems into deployed models that drive multi-million-dollar planning decisions every day. As a Data Scientist II, you will own the end-to-end Machine learning Operation cycle: Design, build, and ship machine learning and/or optimization models that directly shape Amazon's middle miles planning decisions. You will own end-to-end delivery — from problem framing with business partners, through modeling and validation, to deployment in internal model hosting platform and integration with downstream planning tools. You will work on problems such as: - Long- and short-horizon forecasting - Network and capacity optimization - GenAI / agentic systems - Defect prevention and adaptive planning You will partner closely with Engineering, Product, Engineering, and stakeholders to translate ambiguous operational pain points into measurable model outcomes. Key job responsibilities - Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model); - Drive end-to-end delivery of scalable models — from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring; - Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization; - Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure; - Define and own model performance metrics (e.g., WAPE) tied to business outcomes; - Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD; - Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.