Senior Applied Scientist, Compliance Shared Service
DESCRIPTION
Amazon's Compliance Shared Service (CoSS) Team is looking for a smart, energetic, and creative senior Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team in Seattle. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance.
You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog.
Key job responsibilities
- Research on and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model.
- Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases
- Lead and collaborate with product, and tech partners to implement new product features in production.
- Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust.
- Analyze and convey results to stakeholders and contribute to the research and product roadmap.
- Publish research publications at internal and external venues.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 3+ 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
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in Large Language Models: Improving the state-of-the-art methods in in-context prompting, fine-tuning, multi-modal modeling etc.
- Experience defining organizational research and development roadmap and practices in industry
- Ability to work on a diverse team or with a diverse range of coworkers
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.