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Do you want to be part of a team building machine learning applications that process and analyze transactions worth billions of dollars a day using the latest technology Do you want to make a tangible impact measured in terms of millions of dollars saved
In our Finance Technology group, we develop machine learning systems that scrutinize billions of dollars in transactions from across Amazon's businesses. Our mission is to drive wider adoption of machine learning solutions for finance processes. We build applications utilizing advanced techniques like forecasting, classification, and anomaly detection. Our current projects range from identifying anomalies in data to predicting optimal cash levels for accounts. We utilize the newest tools and technologies such as Generative AI and Large Language Models.
On a typical day, you'll collaborate closely with machine learning scientists, fellow software engineers, and finance teams across Amazon. You'll work with massive datasets in the terabytes range, developing robust machine learning pipelines to process billions in transaction value. We emphasize partnering with our internal customers, so you'll interact directly with them to understand requirements and get feedback.
Our team thrives on innovation, and we're open to new approaches. You'll have opportunities to test your ideas in production environments dealing with real financial data and processes. Join us to apply advanced machine learning capabilities that drive efficiencies and insights for Amazon's finance operations at a massive scale.
Key job responsibilities
In this role, you will participate in all parts of the software development process, from collaborating with customers on design to executing that design in a scalable and extensible way. You will have the opportunity to detect fraudulent transactions/vendors by applying machine learning techniques and help Amazon business every day.
A day in the life
In a typical day, you will work with machine learning scientists, other software engineers, and business groups across Amazon Finance Operations. You will work with terabytes of data and develop machine learning pipelines which process billions of dollars. We partner with our customers, so you will meet with them directly to gain direct feedback on your work. Our team and customer are comfortable trying new ideas, so you will test your ideas in the real world.
About the team
Our team owns machine learning applications and we work with finance operations to prevent, recover, or avoid internal and external theft, fraud, abuse, and waste.
- 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
- 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
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Experience in processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution)
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 for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Job ID: 148782081
Skills:
Distributed Systems, Design Patterns, Machine Learning, generative AI
Skills:
containerization , Kafka, Cloud Technologies, Microservices, Distributed Systems, Elasticsearch, Tls, Python, AWS, Oauth, Java, Ipsec, virtualization, Network Protocols, SSL, Gcp, Spark, Azure, Kubernetes, security principles, real-time analytics, Go, Beam, Pub Sub, pub sub platforms, Pulsar, in-house APIs, big data pipelines, distributed architectures, distributed datastores
Skills:
Java, Machine Learning, Python, Sdlc, Relational and NoSQL Databases, Agile Practices, Unit Testing Techniques
Skills:
Kafka, Nosql, Docker, Elasticsearch, Python, AWS, Java, Oauth, Graphql, Scala, Sql, REST, Gcp, Spark, Azure, Kubernetes, embeddings, pgvector, Pinecone, Flink, OpenSearch, Beam, LLMs, FAISS, RAG, Milvus, Weaviate
Skills:
Machine Learning, modern web development technologies, Generative AI, data-driven systems, distributed systems software, intelligent automation
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