Machine Learning Engineer, Amazon Business, AB - Prime, SSR, Emerging
Job ID: 2882424 | Amazon.com Services LLC
Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.
Amazon Business (www.amazon.com/business) is an online store that combines the selection, convenience and value customers have come to know and love from Amazon, with new features and unique benefits tailored to the needs of businesses. Amazon Business provides easy access to hundreds of millions of products – everything from IT and lab equipment to education and food-service supplies. Our customers range from government entities with tens of thousands of users to sole proprietors.
We are looking for a Machine Learning Engineer (MLE) to join the team to drive key science methods and delivery of the project, working closely with science, product and engineering leads, as well as our leadership. We’re a fast-growing team with high visibility from the leadership team and lots of new opportunities.
Key job responsibilities
1. Lead end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
2. Focus on Model Deployment, including all tasks necessary to turn a prototype into a production model, such as:
1. Model data pipelines: building data pipelines to produce inputs for training and inference in both online and offline contexts.
2. Training and inference pipelines: orchestration of model training and inference jobs.
3. Post-inference work: work required after the model’s output to serve business needs such as integration with engineering systems.
3. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
4. Contribute to our ML Infrastructure, such as enhancements to our live model and experimentation platform.
5. Maintenance and Operational Excellence: Regular maintenance and monitoring expected of any complex system/service.
6. Contribute to building an infrastructure that facilitates end-to-end ML workflows.
About the team
The Marketing Science team applies scientific methods and research techniques to enhance our understanding of AB consumer behavior, market trends, and the effectiveness of marketing strategies. Our goal is to develop and advance theories and models that can be used to make informed decisions in marketing and to provide insights into consumer decision-making processes.
BASIC QUALIFICATIONS
1. 3+ years of non-internship professional software development experience.
2. 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
3. Experience programming with at least one software programming language.
PREFERRED QUALIFICATIONS
1. 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
2. Bachelor's degree in computer science or equivalent.
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.
Posted: January 29, 2025 (Updated about 3 hours ago)
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