Sr. Applied Scientist, Generative AI Innovation Center

Amazon; London; On-site; GBP 60,000 - 100,000; Full time

Job description

Sr. Applied Scientist, Generative AI Innovation Center

Job ID: 2930123 | Amazon Web Services Korea LLC

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for Sr. Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Key job responsibilities

As an Applied Scientist, you will:

1. Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges.
2. Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production.
3. Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder.
4. Provide customer and market feedback to product and engineering teams to help define product direction.

A day in the life: This is a customer facing role. You will be required to travel to client locations and deliver professional services as needed.

BASIC QUALIFICATIONS

- PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, OR Masters degree plus 10 years of relevant work experience.
- 5+ years of hands on experience with Python to build, train, and evaluate models.
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
- Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies.
- Experience in patents or publications at top-tier peer-reviewed conferences or journals.

PREFERRED QUALIFICATIONS

- Experience with the design, deployment, evaluation, and optimization of Large Language Model (LLM)-powered agents, tools, and orchestration approaches, including the development of high-quality prompts and templates to guide the behavior and responses of LLMs.
- Experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools.
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
- Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts.
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

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.