Senior Applied Scientist, SPEED
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 Framework, Ads Design System, Ads Portal Spoofing), Ads Portal Common Experience Systems (Ads Portal Navigation, Ads Notifications, Advertiser Feedback System) and Ads Portal Analytics & Science Framework (Telemetry, Observability, Experimentation, Insights). 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. It helps builders uncover the unknown by scientifically measuring customer experience at all stages of their journey within Ads self-serve and making it easily accessible.
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. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.
Key Responsibilities:
- Map business requirements and customer needs to a scientific problem.
- Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization.
- Research, design and implement scalable machine learning (ML), natural language, or computational models to solve problems that matter to our customers in an iterative fashion.
- Mentor and develop junior applied scientists and developers who work on applied science problems in the same organization.
- Stay informed on the latest machine learning, natural language and/or artificial intelligence trends and make presentations to the larger engineering and applied science communities.
You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements.
Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
Team video https://youtu.be/zD_6Lzw8raE
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience in building machine learning models for business application
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 $150,400/year in our lowest geographic market up to $260,000/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.