Description
Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Ads Self-serve Products for Experience, Experimentation, and Developer productivity (Ads SPEED) team drives a coherent experience across Amazon Ads Console for all endemic and non-endemic advertisers and their agencies using Amazon’s marketing portfolio to grow their business and brands on and off Amazon. We enable Ad application builders across every product development cycle stage — from decisions to build, to launch and ongoing product health monitoring and troubleshooting.
We have three programs – Ads Portal Foundation Systems, Ads Portal Common Experience Systems, and Ads Portal Analytics & Science Framework. Our foundation charter builds common features that form the home for all Amazon Ads products and applications. It accelerates federated innovation and enables all builders to ship applications for customers globally while keeping the overall Ads Portal experience familiar. Experience charter builds and enhances marketer experiences across Ads Portal. Analytics & Science charter empowers builders to make data-informed product decisions through the next generation of analytics technologies and experimentation capabilities.
We seek a strong technical leader with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models.
Key job responsibilities
As a Principal Applied Scientist, you will have deep expertise in machine learning and data science, with specialties in large language models, reinforcement learning, supervised learning, and generative AI across various modalities. This role involves aligning solutions with multiple partners including product teams, experience design and foundational model teams. You will lead teams of scientists and engineers in translating business and functional requirements into concrete deliverables, driving strategic initiatives to enhance Gen AI driven advertiser experiences.
Your responsibilities include designing integrated solutions that are efficiently implemented across all stakeholder teams, maintaining alignment in the short term while influencing long-term strategic roadmaps to support ongoing experimentation. You will ensure high solution quality, focusing on accurately understanding and responding to stakeholders, enhancing the speed of experiments and iterations of advertiser experience.
Additionally, this role involves building scalable solutions with robust checks on human feedback, managing the complexities of user intents, and reinforcing learning algorithms with human feedback. You will make critical decisions on the best technical solutions for both immediate and future needs, clarify complex issues, manage trade-offs, and communicate effectively about technical challenges.
Finally, you will work with academic partners to enhance our team's capabilities by accessing the latest research and expert mentoring, ensuring our approaches remain cutting-edge.
We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA.
Basic Qualifications
- PhD degree in Computer Science, Math, or a related field.
- Experience in developing large language models and reinforcement learning solutions for generative AI applications.
- Experience in developing AI, ML, and NLP systems, with a proven ability to deliver projects successfully.
- Skilled in managing large, cross-functional projects with evolving requirements from start to finish.
- Strong foundations in data structures, algorithm design, and complexity analysis.
- Ability to strategize for ML platforms focusing on recommender systems, ranking, and customer interaction features.
- Exceptional ability to understand customer needs, propose alternative technical and business solutions, and deliver on tight deadlines.
- Record of peer-reviewed scientific publications in applied science.
Preferred Qualifications
- Over 10 years of post-PhD research experience in machine learning.
- Strong mathematical and statistical skills.
- Profound knowledge of foundational models, including large language models across multiple modalities, reinforcement learning, supervised learning, and other cutting-edge techniques in generative AI.
- Demonstrated success in algorithm design and product development.
- Publications in top-tier conferences or journals.
- Experienced in mentoring and managing senior technical staff.
- Proven business acumen, balancing multiple aspects of projects including technology and product strategies.
- Effective communicator with diverse audiences.
- Experience with large data sets and building scalable models.
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 $179,000/year in our lowest geographic market up to $309,400/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.
Company: Amazon.com Services LLC
Job ID: A2660796
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