Amazon's mission is to be Earth’s most customer-centric company. We use data to anticipate customer needs, create technology solutions for customer engagement, and personalize customer experiences.

Join an innovative and passionate team building the next generation of intelligent systems for customer service at Amazon. The Customer Service AI Training & Evaluation team is looking for Software Developers passionate about Machine Learning and Natural Language Processing. We are looking for versatile and passionate engineers who are customer-centric, and looking to solve never-before-solved problems. You will enjoy a small-team environment that balances research with application; you will explore the frontier of Machine Learning techniques and take what you have found to solve real-world problems. Your work will have a direct impact on the bottom line of our business while improving customer experience. If big data, cutting edge technologies and building intelligent systems excite you, if you love to innovate and deliver results, then we want you to be on our team.

If this sounds interesting, we’d love to hear from you.


Major Responsibilities
- Develop and Implement predictive simulation and evaluation models for real time customer support predictions
- Boost Innovation by building rapid prototypes for experimentation
- Use statistics, NLP and machine learning techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of both structured and unstructured data to help automate and optimize key processes
- Design, experiment and evaluate highly innovative models for predictive learning
- Work closely with business staff to optimize various business operations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation


Key job responsibilities
- Collaborate with science and engineering teams to develop and integrate platform features that enable teams to train, evaluate, and deploy high quality machine learning/LLM conversational customer support agents that participate in real-time contact resolution
- Work closely with Applied Scientists to ensure functioning dependencies for training and evaluation are met for foundational model training and fine-tuning, in-context learning, and prompt engineering
- Drive system architecture, spearhead best practices, and mentor junior engineers.

A day in the life
As a SDE with the CSAI Training & Evaluation team, you will be responsible for development of high performance, low latency, cutting edge machine learning conversational customer support customers and agents - which help customers resolve problems. Your work will directly impact our retail ordering, digital, seller, and driver services - through enabling the use of automated conversational agents that participate in text and voice contact resolution. You will drive system architecture decisions, and contribute to best practices that enable a quality training, evaluation and deployment infrastructure.

“If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!”Benefits Summary:
“Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan”

About the team
Join our team and work at the forefront of AI. Collaborate with top minds pushing boundaries in LLM training and evaluation of customer support models. This is a unique opportunity to create history and shape the future of artificial intelligence in customer support.

Our team accelerates sciences ability to train large language models while maintaining and improving the model quality bar. We automate measuring & evaluating quality against a baseline of what good contact handling looks like, detecting drift, and triggering retraining. We track the training data and prompt lineage, so we can evaluate and optimize model performance.