Job Information
Amazon Software Development Engineer, Conversational AI Modeling and Learning in Seattle, Washington
Description
The Conversational AI Modeling and Learning (CAMEL) team is looking for a passionate, talented, and inventive SDE/MLE to play pivotal role in the development of industry-leading, Generative AI (GenAI) powered conversational assistant capabilities using latest techniques like fine tuning, ICL (In Context Learning) and various prompt optimization techniques.
Key job responsibilities
Ability to quickly learn cutting-edge technologies and algorithms in the field of Generative AI to participate in our journey to build the best conversational agent.
Responsible for the development and maintenance of key platforms needed for developing, evaluating and deploying large language models required for building conversational agents.
Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.
Work closely with Applied scientists to process massive data, scale machine learning models along with optimizing latency, cost and capacity.
Work in an Agile/Scrum environment to deliver high quality software against aggressive schedules.
A day in the life
As a SDE with the CAMEL team, you will be responsible for leading the development of high performance, low latency, cutting edge model routing solutions to advance the state of the art Conversational agents. Your work will directly impact our customers in the form of products and services that make use of conversational agent innovations. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI) to improve Conversational Excellence. You will have significant influence on our overall strategy by helping define data, enrichment, model optimizations and evaluation. You will drive the system architecture, and spearhead the best practices that enable a quality infrastructure.
About the team
Join our CAMEL team and work at the forefront of AI. Collaborate with top minds pushing boundaries in deep learning, reinforcement learning, and more. Gain valuable experience and accelerate your career growth. This is a unique opportunity to create history and shape the future of artificial intelligence.
Basic Qualifications
3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
Preferred Qualifications
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
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 $129,300/year in our lowest geographic market up to $223,600/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.