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Lead Applied Scientist in Generative AI Solutions
2 months ago
Amazon Worldwide Advertising is recognized as one of the fastest expanding and most lucrative sectors within Amazon. The Ads Self-serve Products for Experience, Experimentation, and Developer Productivity (Ads SPEED) team is dedicated to creating a seamless experience across the Amazon Ads Console for all advertisers and their agencies, leveraging Amazon's marketing tools to enhance their business and brand visibility both on and off the platform. Our team supports Ad application developers throughout every stage of the product development lifecycle — from conceptualization to launch and continuous product performance monitoring and troubleshooting.
We are in search of a proficient technical leader with specialized knowledge in machine learning and deep learning, including transformers, generative models, large language models, computer vision, and multimodal models. You will be responsible for developing innovative solutions at scale, pushing the boundaries of technology and science. Your role will involve guiding the design, modeling, and architectural decisions for cutting-edge large language models and multimodal frameworks. You will implement new algorithms and learning strategies while being actively involved in the execution from ideation to deployment.
Key Responsibilities:
As a Lead Applied Scientist, you will possess extensive expertise in machine learning and data science, with a focus on large language models, reinforcement learning, supervised learning, and generative AI across various modalities. This position requires collaboration with multiple partners, including product teams and foundational model teams. You will lead teams of scientists and engineers in transforming business and functional requirements into tangible outcomes, driving strategic initiatives to enhance AI-driven advertiser experiences.
Your responsibilities will include designing integrated solutions that are effectively implemented across all stakeholder teams, ensuring alignment in the short term while influencing long-term strategic roadmaps to support ongoing experimentation. You will maintain high solution quality, emphasizing a clear understanding of stakeholder needs, and enhancing the speed of experiments and iterations of advertiser experiences.
Additionally, this role entails developing scalable solutions with robust mechanisms for human feedback, managing the complexities of user intents, and reinforcing learning algorithms with human insights. You will make critical decisions regarding the most suitable technical solutions for both immediate and future requirements, clarify complex issues, manage trade-offs, and communicate effectively about technical challenges.
Finally, you will collaborate with academic partners to elevate our team's capabilities by accessing the latest research and expert guidance, ensuring our methodologies remain at the forefront of innovation.
BASIC QUALIFICATIONS:
1. PhD in Computer Science, Mathematics, or a related discipline.
2. Proven experience in developing large language models and reinforcement learning solutions for generative AI applications.
3. Expertise in AI, ML, and NLP systems, with a successful track record of project delivery.
4. Proficient in managing large, cross-functional projects with evolving requirements from inception to completion.
5. Strong foundation in data structures, algorithm design, and complexity analysis.
6. Ability to strategize for ML platforms focusing on recommender systems, ranking, and customer interaction features.
7. Exceptional capability to understand customer needs, propose alternative technical and business solutions, and deliver under tight deadlines.
8. Record of peer-reviewed scientific publications in applied science.
PREFERRED QUALIFICATIONS:
1. Over 10 years of post-PhD research experience in machine learning.
2. Strong mathematical and statistical acumen.
3. In-depth knowledge of foundational models, including large language models across multiple modalities, reinforcement learning, supervised learning, and other advanced techniques in generative AI.
4. Demonstrated success in algorithm design and product development.
5. Publications in top-tier conferences or journals.
6. Experience in mentoring and managing senior technical staff.
7. Proven business acumen, balancing multiple aspects of projects including technology and product strategies.
8. Effective communicator with diverse audiences.
9. Experience with large datasets and building scalable models.
Amazon is committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
