Job Information
Amazon Senior Applied Scientist , Enterprise Engineering in Seattle, Washington
Description
Are you a scientist interested in pushing the state of the art in computer vision, ML, or LLMs? Are you interested in working on ground-breaking projects that will lead to great product? Do you wish you had access to large datasets? If you answered "yes" to any of these questions, join Amazon's leading-edge SaaS eDiscovery platform team as a Senior Applied Scientist to drive innovation using LLM and GenAI. Your work will have a direct impact on streamlining data discovery, and ensuring Amazon remains ahead of the curve in legal and security risk management.
We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of LLMs and the related foundational models to augment generative text, imagery, and videos.
You must have deep technical experience working with methods and technologies related to Large Language Models (LLMs), experience of building models for business applications and research. This includes fine-tuning and prompt engineering. You will regularly engage with managers, who will partner with you to productionize your work.
Key job 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.
Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity.
Contribute to build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.
Work closely with software engineering teams to deploy your innovations.
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.
About the team
The Enterprise Engineering organization is looking for an experienced Applied Scientist with a strong background in cloud platforms development and AI/ML. We are using AWS products to evolve traditional enterprise tools and services or building new high-performance services – if you are passionate about Amazon and have experience building critical services at global scale, this is the team for you.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
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
Research expertise in computer vision 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 machine learning systems such as profiling and debugging and understanding of system performance and scalability
Experience using managed ML/AI solutions
Strong skills in problem solving, programming, and computer science fundamentals
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 $136,000/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.