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Sr. Responsible AI Data Scientist, Generative AI Innovation Center

2 months ago

Seattle, United States Amazon Full time

This is an exciting opportunity to shape the future of AI and make a real impact on our customers' generative AI journeys. Join the Generative AI Innovation Center to help customers shape the future of Responsible Generative AI 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.

AWS Generative AI Innovation Center is looking for a Generative AI Data Scientist, who will guide customers on operationalizing Generative AI workloads with appropriate guardrails and responsible AI best practices, including techniques for mitigating bias, ensuring fairness, vulnerability assessments, red teaming, model evaluations, hallucinations, grounding model responses, and maintaining transparency in generative AI models. You'll evangelize Responsible AI (RAI), help customers shape RAI policies, develop technical assets to support RAI policies including demonstrating guardrails for content filtering, redacting sensitive data, blocking inappropriate topics, and implementing customer-specific AI safety policies. The assets you develop, will equip AWS teams, partners, and customers to responsibly operationalize generative AI, from PoCs to production workloads. You will engage with policy makers, customers, 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, Innovation Center, you will interact with AI/ML scientists and engineers, develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You may also create enablement materials for the broader technical field population, to help them understand RAI and how to integrate AWS services into customer architectures.

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.

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.

Key job responsibilities

- Guide customers on Responsible AI and Generative AI Security: Act as a trusted advisor to our customers, helping them navigate the complex world of Generative AI and ensure they are using it responsibly and securely.
- Operationalize generative AI workloads: Support customers in taking their generative AI projects from proof-of-concept to production, implementing appropriate guardrails and best practices.
- Demonstrate Generative AI Risks and Mitigations: Develop technical assets and content to educate customers on the risks of generative AI, including bias, offensive content, cyber threats, prompt hacking, and hallucinations.
- Collaborate with GenAI Product/Engineering and Customer-Facing Builder Teams: Work closely with the Amazon Bedrock product and engineering teams and customer-facing builders 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.

About the team
About 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Bachelor degree in Business, Science or related technical, math, or scientific field