דרושים Applied Scientist International Machine Learning ב-אמזון ב-India, Manesar

Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications.Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services.You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements.

- 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Master's degree in math/statistics/engineering or other equivalent quantitative discipline, or PhD

Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications.Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services.You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements.

- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals

Key job responsibilities

- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals

Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications.Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services.You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements.

- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- Experience using Unix/Linux
- Experience in professional software development
- PhD, or a Master's degree and experience building machine learning models or developing algorithms for business application
- Significant peer reviewed scientific contributions in relevant field
- Extensive experience applying theoretical models in an applied environment
- Expertise on a broad set of ML approaches and techniques
- Prior Experience in Transportation Logistics business
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

Key job responsibilities
As an Applied Scientist in Amazon Autos, you will:
- Drive big picture innovations with clear roadmaps for intermediate delivery.
- Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation.
- Interface with business customers, gathering requirements and delivering science solutions.
- Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.
- Effectively communicate complicated machine learning concepts to multiple partners.
- Research new and innovative machine learning approaches.A day in the lifeYour science expertise will be leveraged to research and deliver novel solutions to existing problems, explore emerging problem spaces, and create new knowledge. You will invent and apply state-of-the-art technologies, such as large language models, machine learning, natural language processing, and computer vision, to build next-generation solutions for Amazon.
You'll publish papers, file patents, and work closely with engineers to bring your ideas to production.

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Every day will bring new and exciting challenges on the job while you:* Provide field support to resolve inquiries from Enterprise customers regarding AWS service or Cloud.
* Complete analysis and present periodic reviews of operational performance to customer
* Provide detailed reviews of service disruptions, metrics, detailed prelaunch planning
* Ensure AWS environments remain operationally healthy whilst reducing cost and complexity
* Foster trusting relationships with customers, understanding their business needs and technical challenges
* Lead technical discussions with senior leadership regarding incidents, trade-offs, and risk management
* Work directly with AWS global engineering and service teams to resolve customer issue.
TAM 으로서 여러분은 고객이 EC2, RDS 데이터베이스, ECS/EKS, IoT, 보안/거버넌스 등 다양한 AWS 서비스를 도입 및 사용할 수 있도록 전략의 수립 및 이행을 지원하게 됩니다. 기술적 및 고객 응대 역량을 발휘하여 고객사 환경 내에서 AWS를 효과적으로 대표하고 사고/장애, 트레이드 오프 및 리스크 관리에 대하여 시니어 리더십과의 논의를 주도합니다. 표준적인 방법론을 활용하여 솔루션 기획, 빌드에 있어 전략/기술적 방향성 및 변론을 제공하고, 고객의 AWS 운영 환경을 양호하게 유지하기 위해 적극적으로 개입합니다. 고객과 긴밀한 협력 관계를 구축하여 고객의 비즈니스/운영상의 필요와 기술적 해결 과제를 파악하고 AWS에서 최대한의 가치를 실현할 수 있도록 보조합니다.우리 팀에서는 IT 아키텍팅 및 운영 (OS/미들웨어/DB/네트워크 관리, 고객센터 시스템/어플리케이션 관리 등 유관 분야) 에 해박한 배경지식을 지닌 후보자를 찾고 있습니다. Enterprise Support 가 고객에게 가치를 제공함에 있어 TAM으로서 중점적 역할을 맡아 혁신의 최전선에서 함께 하고싶은 분이라면 누구나 환영입니다.여러분은 다음과 같은 직무를 수행하며 매일 새롭고 가슴 뛰는 도전을 하게 될 것입니다:* 현장 지원을 통해 AWS 서비스 및 클라우드 관련한 기업 고객의 요청/문의 해결
* 운영상의 퍼포먼스에 대한 완전한 분석 및 주기적 검토 결과를 고객에게 제공
* 서비스 중단, 지표 및 구체적인 론칭 전 계획에 대한 자세한 검토 수행
* 비용 및 복잡성을 낮추는 동시에 AWS 환경이 운영상 양호한 상태를 유지하도록 보장
* 고객과 신뢰관계를 구축하고 고객의 비즈니스 니즈 및 기술적 해결과제를 파악
* 사고/장애, 트레이드 오프 및 리스크 관리와 관련하여 시니어 리더십과 기술적 논의를 주도
* AWS 글로벌 엔지니어링 및 서비스 팀과 직접 협력하여 고객 이슈 해결A day in the life
[English Version]
* Educational Program
- You will be given a Ramp-up period for 90 days when you onboard. During this period, you will learn skills and process needed for customer support and also AWS cloud service/solution thru various education and practice
* Career Opportunity
* Work and Life Harmony* Mentorship & Career Growth
[Korean Version]
* 교육 프로그램
- 온보딩 시 90일간의 집중 교육 기간을 거치게 됩니다. 이 기간 동안 고객 지원에 필요한 스킬 및 프로세스와 AWS 클라우드 서비스 및 솔루션에 대해 다양한 교육 및 실습을 통해 배울 수 있습니다.
- 우리 팀에서는 고객 지원 경험이나 기술 지식 세션 등 지식 및 경험 공유를 권장하고 있습니다.
- AWS에서는 다양한 자기 개발 프로그램을 제공합니다. AWS가 제공하는 영어 교육 프로그램은 직원들이 글로벌 엔지니어링 및 서비스 팀과 협업하는 데 필요한 비즈니스 영어 역량을 향상시킵니다.
* 커리어 기회
- AWS의 글로벌 엔지니어링 팀과 적극적으로 커뮤니케이션 및 협업 할 수 있습니다.
- 다른 AWS 리전에서도 근무해 볼 수 있도록 내부적으로 해외 발령 기회를 제공합니다.
* 일과 삶의 조화
- 우리 팀은 일과 삶의 균형을 중시합니다. 중요한 것은 단순히 집에서 혹은 회사에서 얼마나 많은 시간을 보냈는지가 아니라, 일과 삶 두 측면에 모두 에너지를 분배할 수 있도록 흐름을 만드는 것입니다. 우리는 행복하고 만족스러운 삶을 위해서는 개인적 삶과 일 간의 적절한 균형이 필수적이라 믿으며, 근무시간의 유연성을 제공하고 각자가 자신에게 맞는 일과 삶의 균형점을 찾아가도록 권장합니다.
* 멘토링 & 커리어 성장
- 우리 팀에서는 멘토링, 교육 세미나 등 다양한 프로그램을 통해 개개인의 커리어 성장을 지원합니다. 다양한 경험, 근속 기간을 지닌 분들이 함께 일하고 있으며 멘토링을 통해 지식과 경험을 공유할 수 있는 환경을 구축해 나가고 있습니다. 우리 팀에서는 개개인의 커리어 성장을 중시하며 프로젝트 할당을 통해 각자가 다방면에 걸친 전문가로 성장할 수 있도록 노력하고 있습니다.
* 해당 직무는 Korea Enterprise Support 팀 소속입니다. Enterprise Support팀은 아마존 웹 서비스(AWS) 내에서 가장 빠르게 성장하고 있는 조직 중 하나로 산업 부문이나 규모를 막론하고 모든 고객사가 AWS로부터 최선의 가치와 서비스를 제공받을 수 있도록 지원합니다. AWS Enterprise Support 팀에서는 컴퓨트, 스토리지, 데이터베이스, 데이터 애널리틱스, 애플리케이션 레벨 서비스, 네트워킹, 서버리스 등 다양한 테크놀로지 영역 전반에서 고객의 혁신을 함께할 Technical Account Manager (TAM)을 채용 중입니다. TAM은 세일즈 직무가 아니며, 주요한 기술 고문이 될 수 있는 기회로서 스타트업에서 대기업에 이르기까지 디지털 전환의 여정을 이제 막 시작한, 또는 이어 나가고 있는 다양한 규모의 고객에게 ‘고객의 목소리’가 되어줄 수 있습니다.

. Experience with operating and troubleshooting in at least three of the following areas: compute, storage, networking, CDN, databases, DevOps, big data and analytics, security, or application development in a distributed systems environment.
. Fluent in both English and Korean

Key job responsibilities
QAEs in our team are responsible for driving our software development process toward quality-centric methodologies and for reporting on test progress, metrics, issues and risks., writing test cases, test plan and test strategy that are of high quality, and maintainable. You are able to reproduce product defects & script failures to assist developers or other testers and identify, track, and accurately report defects found. You create automation scripts for low complexity test cases based on feasibility analysis done by the QA / DEV teams. You acquire knowledge of the features and detailed functional requirements of the work to execute your assigned tests, and find gaps in the test plan/test coverage. You have the ability to deep dive on applications, comparing features between various versions & identifying changes made within versions.

- 1+ years of quality assurance engineering experience
- Experience in automation testing
- Experience in manual testing
- Experience in UI and API automation testing (Selenium/SOAPUI)

- Experience in API & Mobile testing
- Experience designing and planning test conditions, test scripts, and test data sets to ensure appropriate and adequate coverage and control