Jobs for People with MS: National MS Society

Description

Are you passionate about Generative AI (GenAI)? Do you want to help some of our most strategic customers adopt this technology? In this role, you will help our customers build and deploy GenAI enabled applications using Amazon Bedrock and SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power applications. You will engage with product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.

At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.

AWS is looking for a Generative AI Data Scientist, who will be the Subject Matter Expert (SME) for helping customers in designing abd optimizing solutions that leverage our Generative AI services. As part of the Worldwide Specialist Solutions Architecture team, you will work closely with other Specialist Machine Learning Architects from various geographies to enable large-scale customer use-cases and drive the adoption of Amazon Web Services for ML/AI platforms. You will partner with Solution Architects and other Data Scientists 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 ML solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review. You may continue to sponsor the creation of new products and features from these requirements, working closely with product and engineering teams to minimize requirements drift from your customer’s needs.

You must have deep technical experience working with technologies related to multimodal, image generation, from model fine-tune to prompt engineering. 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 AI/ML 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, with the ability to impress Amazon Web Services customers at any level, from executive to developer. 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 ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation.

Key job responsibilities

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

• Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements.

• Act as a technical liaison between customers and the AWS Bedrock service teams to provide customer driven product improvement feedback.

• Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.

• Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers and with the academic community.

About the team

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.

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.

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.

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.

Basic Qualifications

• 5+ years of Data Scientist or Machine Learning Solutions Architect experience

• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

• Hands-on experience in developing models, in optimizing model training and tuning and in deploying LLMs such as GPT, LLaMA, Falcon, BERT, or Transformer-based architectures

• Strong background in Natural Language Processing, including experience with text representation, language modeling, sequence-to-sequence architectures, and semantic understanding

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

Preferred Qualifications

• Experience as a leader and mentor on a data science team

• Active in the open source community, such as HuggingFace, StableDiffusion, etc

• Large models pretrain/fine-tuning experience, familiar with distributed training

• Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM. Craft prompts to elicit specific information or control the model's output, ensuring desired accuracy, relevance, and language fluency

• Customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, best practices, and risk mitigation. Should be able to interact with Chief Data Science Officers, Chief Marketing Officers, Chief Risk Officers, Chief Technology Officers, and Chief Information Officers, as well as the people within their organizations.

• Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment. Track record of thought leadership and innovation around Machine Learning.

• Experience with LangChain, LLAMAIndex, Foundation model tuning, Data Augmentation, and Performance Evaluation frameworks

• Led a cloud initiative as an AWS customer or consulting with a customer in their own IT transformation.

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/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.