Jobs for People with MS: National MS Society

Description

About Amazon Web Services Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud. AWS has been continually expanding its services to support virtually any workload, and it now has more than 240 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, media, and application development, deployment, and management from 105 Availability Zones within 33 geographic regions, with announced plans for 18 more Availability Zones and 6 more AWS Regions in Malaysia, Mexico, New Zealand, the Kingdom of Saudi Arabia, Thailand. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. To learn more about AWS, visit aws.amazon.com.

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Amazon Web Services came to China in 2013, and has been relentlessly investing and expanding our infrastructure and business since then. Amazon Web Services launched its China (Beijing) Region (operated by Sinnet) in September 2016 and its China (Ningxia) Region (operated by NWCD) in December 2017. In 2019, Amazon Web Services added a new region in Hong Kong, making China the only country with three Amazon Web Services regions aside from the U.S. In 2022, Amazon Web Services launched Local Zone in Taipei. Amazon Web Services has also established an AI lab in Shanghai and two IoT labs in Shenzhen and Taipei. The Amazon Web Services Partner Network has thousands of Partners in China. Amazon Web Services has supported over 10,000 local startups and has provided cloud skills training to over 700,000 talents. Amazon’s first two utility-scale renewable projects—a solar farm and a wind farm—are also generating clean energy to the country’s grid.

Do you have a builder’s mentality where “show me” means more than “tell me”? Are you passionate about Generative AI (GenAI), understand cloud architectures & platforms, and quick to pick up emerging technologies? Are you adept at working with Customers to experiment with innovative approaches and the validate the technical feasibility of solutions?

Generative AI is rapidly growing in importance. We’re seeing more and more amazing GenAI work being done from AI-beings APP and intelligence customer service chatbot to operational data analysis, code generation and multimodal implementations. Given the scale required for developing GenAI workloads, the cloud is an ideal place to build them, and Amazon Web Services is the leader in this market. We’re looking for someone passionate and deeply excited about this space. Someone who is devoted to helping IC customers understand how GenAI can make a big difference to their businesses.

Key job responsibilities

• As a Generative AI Specialist Solutions Architect (SA) , you will be the Subject Matter Expert (SME) for designing GenAI solutions that leverage Amazon Web Services. As part of the Specialist Solutions Architecture team, you will work closely with other Specialist SAs to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI platforms.

• You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage ML/AI on Amazon Web Services. You will also create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.

• You must have deep technical experience working with technologies related to Large Language Model (LLM), from model fine-tuning, prompt engineering to end-to-end GenAI solutions. A strong developing machine learning background is preferred, in addition to experience building application and architecture design. You will be familiar with the ecosystem of software vendors in the GenAI space, and will leverage this knowledge to help Amazon Web Services customers in their selection process.

• Candidates must have great communication skills and be very technical and hands-on, with the ability to impress Amazon Web Services customers at any level, from developers to executives. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovations.

About the team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

If you are someone who enjoys innovating, likes solving hard problems and working on the cutting edge of technology, we would love to have you on the team.

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.

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.

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 & 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.

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.

AWS is committed to a diverse and inclusive workplace to deliver the best results for our customers. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status; we celebrate the diverse ways we work. For individuals with disabilities who would like to request an accommodation, please let us know and we will connect you to our accommodation team.

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Basic Qualifications

• 5+ years of experience in design, implementation and consulting experience of Machine Learning/Deep Learning/Generative AI solutions;

• Familiarity with popular commercial/open-source Generative Model and related techniques e.g., Agent, Langchain, vector database, prompt engineering, multimodal, pre-training, fine-tuning etc;

• 2+ years of experience of technical architecture, design, deployment and operational level knowledge;

Preferred Qualifications

• Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.);

• Practical experience of prompt design in production environment, such as templates, instructions, questions and answers, etc., as well as prompt evaluation methods and tools; solid understanding of common machine/deep learning algorithms and hands-on experience in following areas: prompt engineering, BERT, GPT, T5, transformers;

• Experience using Python and/or Java, Go; experience with relational databases, No-SQL, and large-scale distributed systems such as Hadoop and Spark;

• Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format; strong written and verbal communication skills;

• Experience with and Amazon Web Services platform (Amazon SageMaker, EMR, Glue, Lambda, EKS, etc.)