AI/ML Engineer, Professional Services

Amazon.com
서울
2일 전

DESCRIPTION

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help the fastest growing and largest global enterprises derive business value through the adoption of Artificial Intelligence (AI)? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology. We earn trust and credibility with leaders of enterprise customers through our experience working at the enterprise level and our firsthand experience with the challenges of AI adoption.

At AWS, we are looking for AI/ML engineers capable of using AI/ML to design, evangelize, and implement state-of-the-art large-scale AI/ML solutions. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

생성형 AI 알고리즘을 실제 문제 해결에 적용하여 중요한 영향력을 발휘하는 데 관심이 있으신가요? 방대한 양의 데이터를 활용하여 머신러닝(ML)과 딥러닝(DL) 모델을 개발하는 데 흥미를 느끼시나요? 세계에서 가장 빠르게 성장하는 대규모 글로벌 기업들이 인공지능(AI)을 통해 비즈니스 가치를 창출하도록 돕고 싶으신가요? 수십 년간 머신러닝에 투자하며 세계의 AI 기술을 개척하고 형성해 온 아마존의 핵심 일원이 되고 싶으신가요? 우리는 기업 수준의 경험과 AI 도입 과제에 대한 직접적인 경험을 통해 기업 고객 리더들의 신뢰와 신뢰성을 얻고 있습니다.

AWS에서는 AI/ML을 활용하여 최첨단 대규모 AI/ML 솔루션을 설계, 전파 및 구현할 수 있는 AI/Ml 엔지니어를 찾고 있습니다. 고객과 직접 협력하며 혁신적인 프로젝트와 기술에 기여하는 빠른 속도의 조직에서 일하게 됩니다. 실험을 설계하고 실행하며, 새로운 알고리즘을 연구하고, 위험, 수익성 및 고객 경험을 최적화하는 새로운 방법을 찾게 될 것입니다.

Key job responsibilities
  • Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI/ML algorithms to address real-world challenges
  • Interact with customers directly to understand the business problem, help and aid them in implementation of AI/ML solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
  • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
  • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
  • Provide customer and market feedback to Product and Engineering teams to help define product direction

  • AI/ML 과학자, 엔지니어 및 아키텍트와 협력하여 실제 문제 해결을 위한 AI/ML 알고리즘을 연구, 설계, 개발 및 평가
  • 고객과 직접 소통하여 비즈니스 문제를 이해하고, AI/ML 솔루션 구현을 지원하며, 고객에게 브리핑 및 심층 세션을 제공하고 도입 패턴과 프로덕션 경로에 대해 안내
  • 대규모 데이터 분석, 모델 개발, 모델 검증 및 모델 구현을 위한 확장 가능하고 효율적이며 자동화된 프로세스 구축
  • 기술, 비즈니스 및 경영진 이해관계자에 맞춘 모범 사례 권장 사항, 튜토리얼, 블로그 게시물, 샘플 코드 및 프레젠테이션 작성 및 제공
  • 제품 방향 정의를 돕기 위해 고객 및 시장 피드백을 제품 및 엔지니어링 팀에 제공

A day in the life
This is a customer facing role. You will be required to travel to client locations and deliver professional services as needed.

고객을 대면하는 역할이며, 필요에 따라 전문적인 서비스 제공을 위해 고객을 방문해야 할 수 있습니다.

About the team
AWS Global Services

AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.

다양성
AWS는 다양한 경험을 중요하게 생각합니다. JD에 나와 있는 자격 및 기술을 모두 충족하지 못하더라도 지원자가 지원하도록 권장합니다. 경력을 이제 막 시작하였거나, 전통적인 경력을 쌓지 않았거나, 조금 다른 경험을 쌓았다고, 지원을 중단하실 필요는 없습니다.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

AWS를 선택해야 하는 이유
아마존 웹 서비스 (AWS) 는 세계에서 가장 포괄적이고 널리 채택된 클라우드 플랫폼입니다.우리는 클라우드 컴퓨팅 시장을 개척했으며 혁신을 멈추지 않았습니다. 이것이 바로 가장 성공적인 스타트업부터 Global 500 기업에 이르는 고객이 AWS의 제품 및 서비스 제품군을 신뢰하는 이유입니다.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

포용적인 팀 문화
AWS에서는 배우고 호기심을 갖는 것이 우리의 본능입니다.직원이 주도하는 어피니티 그룹은 서로 다른 점을 자랑스럽게 여길 수 있는 포용의 문화를 조성합니다.

Mentorship & 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.

멘토십 및 경력 개발
우리는 세계 최고의 고용주가 되기 위해 노력하면서 지속적으로 성과 기준을 높이고 있습니다.그렇기 때문에 더 다재다능한 전문가로 발전하는 데 도움이 되는 지식 공유, 멘토십 및 기타 경력 개발 리소스를 찾을 수 있습니다.

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.

일과 삶의 균형
우리는 일과 삶의 조화를 중요하게 생각합니다.직장에서의 성공을 위해 가정에서의 희생을 감수해서는 안 됩니다. 그렇기 때문에 유연한 근무 시간과 근무 방식이 우리 문화의 일부입니다.직장과 가정에서 지지받는다고 느낄 때 클라우드로는 달성할 수 없는 것이 없습니다.

#AWSKOREA
#aws-korea-proserv-ap

BASIC QUALIFICATIONS

  • Significant years of industry experience building models for business applications and significant experience with Large Language Models (LLMs) and Prompt Engineering.
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning.
  • Experience in using Python and hands-on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet.
  • Experience using machine learning libraries, such as scikit-learn, NumPy, Pandas, MLlib
  • Strong data engineering skills and communication and Data & AIML presentation skills.

PREFERRED QUALIFICATIONS

  • PhD or Masters degree in computer science, engineering, mathematics, ML operations research, or in a highly quantitative field.
  • Years of industry experience in predictive modeling and analysis, predictive software development.
  • Practical experience in solving complex problems in an applied environment.
  • Prior experience in training and fine-tuning of LLMs.
  • Strong AWS Infrastructure and Automation skills.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Job details

    KOR, Seoul

    Machine Learning Science
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