Description

Are you passionate about Generative AI (GenAI)? This is an exciting opportunity to shape the future of AI and make a real impact on our customers' generative AI journeys. Join our team and play a pivotal role in shaping the future of Responsible Generative AI at AWS while prioritizing security, privacy, and ethical AI practices. In this role, you will play a pivotal role in guiding AWS customers on the responsible and secure adoption of Generative AI, with a focus on Amazon Bedrock, our fully managed service for building generative AI applications.

The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which 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. We work backwards from our customer’s most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam

AWS is looking for a Generative AI Data Scientist, who will guide customers on evaluating foundation models (FMs) from various AI companies for different use cases, analyzing model latencies, and assessing performance across diverse applications.

you will conduct in-depth evaluations of foundation models available on Amazon Bedrock, including those from AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon.. The technical assets you develop, will equip AWS teams, partners, and customers to operationalize generative AI, from PoCs to production workloads. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.

As part of the Generative AI Worldwide Specialist organization, you will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI 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 must have deep understanding of Generative AI models, including their strengths, limitations, and potential risks. You should have expertise in Responsible AI practices, such as bias mitigation, fairness evaluation, and ethical AI principles. In addition you should have hands on experience with AI security best practices, including vulnerability assessments, red teaming, and fine grained data access controls.

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.

Travel up to 40% may be possible.

Key job responsibilities

• Conduct in-depth evaluations of foundation models available on Amazon Bedrock.

• Assess model performance and latency for various industry-specific use cases and develop related technical assets.

• Act as a trusted advisor to our customers, helping them navigate the choice of LLMs, benchmarking methodologies to compare different models capabilities and efficiencies.

• Collaborate with sales and marketing teams to develop and execute go-to-market strategies and sales motions based on model performance insights.

• Assist Amazon Bedrock customers in selecting the most appropriate models for their specific needs and use cases.

• Demonstrate Model Choice, Evaluations, and Performance Benchmarking: Develop technical assets and content to educate customers on model choice, model evaluations, and performance benchmarking for various use cases.

• Collaborate with GenAI Product/Engineering and Customer-Facing Builder Teams: Work closely with the Amazon Bedrock product and engineering teams and customer-facing builders (Solution Architects and Technical Field Community members) to launch new services, support beta customers, and develop technical assets.

• Thought Leadership and External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS re:Invent.

• Develop technical content, workshops, and thought leadership to enable the broader technical community, including Solution Architects, Data Scientists, and Technical Field Community members.

Basic Qualifications

• 5+ years of Data Scientist or Machine Learning Solutions Architect experience preferably with a focus on AI/ML model evaluations, benchmarking, and NLP

• 5+ years of experience with Python to analyze datasets, train , evaluate, deploy, fine-tune, and optimize models.

• Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex, ragas.ai, and other model evaluations frameworks etc.

• Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM.

• Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches.

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

Preferred Qualifications

• Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex, and Whylabs etc.

• Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM.

• Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches

• 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.

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

• Should be able to interact with Chief Data Science 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.

• Familiarity with AWS services and the cloud computing landscape is preferred.

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.

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.