Software Development Engineer - Machine Learning, Customer Engagement Technologies

Amazon is broadly recognized as a leader in providing exceptional Customer Service both in the US and globally. At Amazon, we are driven by innovation and customer obsession, which is deeply ingrained in everything we do, especially in the Customer Engagement Technology (CET) department. Leveraging conversational AI and Machine Learning (ML) technology, we strive to predict and resolve customer issues through self-service and automation solutions.

The Customer Self-Service and Automation team is seeking talented Software Developers who are passionate about applying Machine Learning (ML) and state-of-the-art Large Language Models (LLMs) to resolve customers day-to-day issues.

This role requires expertise in designing and implementing real-time inference services for large-scale conversational AI systems, with a focus on optimizing model performance for low latency and high transactions per second (TPS) in a customer service context. The ideal candidate will have a strong understanding of Large and LLM domain, including experience with model compression techniques, quantization, and efficient serving strategies for conversational AI applications. Ability to balance model accuracy with performance constraints in production environments.

Key job responsibilities
- Work on complex system software, is customer- centric, and feels strongly about building good software as well as making that software achieve its operational goals.
- Build and maintain the inference infrastructure for Amazon's conversational AI customer service chatbots, leveraging LLMs.
- Develop and own the deployment pipelines for integrating and deploying LLM models into production environments, including rigorous testing and validation stages.
- Design and implement the ML inference service that orchestrates the interaction between multiple models, such as issue prediction, item recommendation, and response generation, to provide coherent and contextual responses.
- Integrate with various cross-team services to enable retrieval-augmented generation (RAG) systems, combining language models with external knowledge sources and actuation capabilities to deliver informational and action-oriented responses.
- Enhance observability and logging mechanisms to proactively identify and troubleshoot issues, and maintain dialogue state for offline training and model improvement.
- Collaborate closely with Product Managers, UX designers, Applied Scientists, and experienced Software Development Engineers to effectively apply machine learning models and deliver high-quality conversational AI experiences.

A day in the life
We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.

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 of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.