Description Amazon's Artificial General Intelligence (AGI) Team is responsibly advancing the company’s generative AI technologies, including Amazon’s most expansive multimodal Large Language Models. We are looking for a motivated Machine Learning Engineer that will join our mission by building highly scalable, resilient, and performant training code, systems and infrastructure. You will work in close collaboration with data scientists and research teams to productionize ML models. Key job responsibilities -Design, develop and maintain ML model serving infrastructure to enable high-throughput, low-latency entity resolution predictions in production environments -Collaborate with applied scientists to productionize research models, including implementing model improvements and new architectures for entity matching and deduplication -Develop efficient data processing pipelines to handle large-scale training and inference data for entity resolution models -Support experimentation and A/B testing infrastructure to evaluate model improvements -Work closely with downstream engineering teams to integrate entity resolution capabilities into various product surfaces -Participate in code reviews, technical design discussions, and sprint planning to ensure high quality software delivery -Strong understanding of ML fundamentals and common optimization techniques -Experience with data processing and ETL pipelines at scale - Proven track record of collaborating with data scientists and research teams to productionize ML models 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 - Bachelor's degree in computer science or equivalent - Demonstrated experience with distributed systems and cloud computing platforms (AWS, GCP, or Azure) Preferred Qualifications - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Master's degree in computer science or equivalent - 3+ years of experience deploying and maintaining ML models in production environments 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. 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 $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.