The Shopping Conversation Foundation (SCF) team at Amazon is dedicated to providing foundational capabilities that enable Product, Engineering and Science teams across Rufus, Search, and Alexa Shopping to build, evaluate, and improve large language model (LLM)-based shopping experiences. Our focus areas involve evaluating the quality of the customer experience of AI powered applications, enhancing the customer experience by providing LLMs with up-to-date world knowledge from first-party and third-party data sources, serving high-quality training data for new LLM features (e.g., Multimodal) and Alexa Shopping Remarkable Alexa (RA), and building, serving, and maintaining trustworthy datasets for Rufus and Alexa Shopping.

As a Senior Software Development Engineer in the SCF org, you will specialize in building engineering solutions for information retrieval problems on unstructured and noisy data at internet scale. You’ll tackle challenges such as retrieving relevant information from vast amounts of unstructured data sources like product specifications, expert opinions and customer reviews. You will need to make high-judgment decisions when proposing trade-offs between factors such as computational efficiency, and data privacy, and work closely with cross-functional stakeholders to understand business requirements and propose innovative solutions.

We embrace a collaborative and inclusive culture where diverse perspectives are valued, and creativity thrives. We foster a growth mindset, continuously learning and pushing the boundaries of what's possible in the field of machine learning, generative AI and natural language processing.

Key job responsibilities - Research, design, and develop cutting-edge information retrieval solutions to address complex challenges in the shopping domain, such as retrieving relevant information from unstructured and noisy data sources at internet scale.

- Design, develop, test and deploy large scale distributed data processing systems with reliable performance in production environments.

- Design, develop, test, and deploy inference solutions for high-end large language models (LLMs) and other machine learning models, ensuring efficient and reliable performance in production environments.

- Mentor and guide junior software development engineers, fostering their growth and development through knowledge sharing, code reviews, and hands-on coaching.

- Contribute to the overall growth and development of the team by staying up-to-date with the latest advancements in machine learning, information retrieval, and sharing your expertise through technical presentations, documentation, and training sessions. BASIC QUALIFICATIONS - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team PREFERRED QUALIFICATIONS - 5+ 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 - - Experience with Python, PyTorch, and Java programming and performance optimization - - Excellent problem-solving skills, with the ability to think creatively and critically about complex problems - - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - -Good understanding of Machine Learning and experience with LLMs will be a plus.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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.