Jobs for People with MS: National MS Society

Description

Amazon Web Services (AWS) is looking for an Artificial Intelligence Specialist Solutions Architect (AI SA) with healthcare and life sciences domain expertise. The AI SA will be the Subject Matter Expert (SME) for helping healthcare and life sciences customers design and build machine learning solutions that leverage the AI stack on AWS. You will partner with other SAs, Sales, Business Development and the AI Service teams to enable customer adoption and revenue attainment. You will develop white papers, blogs, reference implementations, labs, and presentations to evangelize AWS AI design patterns and best practices for healthcare and life sciences industry. You will also mentor and train the broader SA population, to help other SA’s understand how to integrate the AI stack into healthcare and life sciences customer architectures. You will have the opportunity to help shape and execute a strategy to build mindshare and broad use of AI on AWS within Healthcare & Life Sciences (HCLS) enterprise customers. This role will work hands-on with machine learning and will connect technology with measurable business value. This position will think strategically about business, products, and technical challenges.

This role will include up to 30% domestic travel.

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 professional and enable them to take on more complex tasks in the future.

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 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.

The AWS Industries team is committed to helping industry customers enable their digital transformation journeys. Our primary goal is to meet customers where they are in their cloud journey and work backwards from their industry specific needs to transform their business and their entire industry. Our team speaks the language of our industry customers, which means that we focus on business outcomes and industry use cases on behalf of our customers, whether that is how we build products and solutions, how we sell, how we deliver, or how we partner.

Key job responsibilities

• Work with customer’s AI team to deeply understand their business and technical needs and build AI solutions that make the best use of the AWS Cloud platform and AI Services.

• Thought Leadership – Evangelize AWS Services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.

• Partner with Generalist SAs, Sales, Business Development and the AI Service teams to accelerate customer adoption and revenue attainment.

• Act as a technical liaison between customers and the service engineering teams and providing produce improvement feedback.

• Develop and support an AWS internal community of AI related subject matter experts.

• In partnership with the sales team, formulate and execute a sales strategy to exceed Global Life Sciences (GLS) revenue objectives through the adoption of AWS

• As a key member of the GLS business development and sales team, ensure success in building and migrating applications, software and services on the AWS platform

• Educate GLS customers on the value proposition of AWS, and participate in deep architectural discussions to ensure solutions are designed for successful deployment in the cloud

• Conduct one-to-few and one-to-many training sessions to transfer knowledge to customers considering or already using AWS

• Capture and share best-practice knowledge amongst the AWS solutions architect community

• Author or otherwise contribute to AWS customer-facing publications such as whitepapers

• Build deep relationships with senior technical individuals within customers to enable them to be cloud advocates

• Act as a technical liaison between customers, service engineering teams and support

We are open to hiring candidates to work out of one of the following locations:

Chicago, IL, USA | New York City, NY, USA | San Francisco, CA, USA | Seattle, WA, USA

Basic Qualifications

- - Relevant experience in machine learning model development lifecycle including (but not limited to) training, fine tuning feature engineering techniques and deployment options

- - Significant hands-on experience with python, R or other programming languages and independently building prototype applications

- - Significant experience building with libraries like PyTorch, Tensorflow, MxNet and ScikitLearn

- - Relevant experience working in specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics)

- - Experience with IT development or implementation/consulting in the software or Internet industries

Preferred Qualifications

- - Deep understanding of neural networks like transformers and the ability to customize them based on a dataset and problem statement.

- - Significant experience in infrastructure architecture, database architecture and networking

- - Experience working with end user or developer communities

Amazon is committed to a diverse and inclusive workplace. 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. 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, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.