Description

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. Amazon Business customers also enjoy a variety of benefits, including business-only pricing and selection, a multi-seller marketplace, single- or multi-user business accounts, approval workflow, purchasing system integrations, payment solutions, tax exemptions, dedicated customer support, Business Prime and more. Our customers range from government entities with tens of thousands of users to sole proprietors.

We are moving fast and have the ability to shape our tech infrastructure that will combine science and scalable engineering at a rapid pace. 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

-Lead end-to-end Machine Learning projects that have a high degree of ambiguity,

scale, complexity.

-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.

-Establish scalable, efficient, automated processes for large-scale data analysis,

machine-learning model development, model validation and serving.

-Contribute to our ML Infrastructure, such as enhancements to our live model and

experimentation platform.

-Maintenance and Operational Excellence: Regular maintenance and monitoring

expected of any complex system/service.

-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. Additionally, we seek to identify and explore emerging trends and technologies in marketing, and to develop innovative approaches for addressing the challenges and opportunities in the field.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA

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

Preferred Qualifications

• 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

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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.