Senior Machine Learning Engineer

Allergan Data Labs is on a mission to transform the Allergan Aesthetics beauty business at AbbVie, one of the largest pharmaceutical companies in the world. Our iconic brands include BOTOX® Cosmetic, CoolSculpting®, JUVÉDERM® and more. The medical aesthetics business is ripe for rapid growth and disruption, and we are looking to add to our high performing team to do just that. 

Our team has successfully launched a new and innovative technology platform, Allē, which serves millions of consumers, tens of thousands of aesthetics providers and thousands of colleagues throughout the US. Since its launch in November 2020, Allē has delivered curated promotions, personalized experiences and had millions of consumers use it as part of their beauty journey. 

We’re looking to add to our team as we prepare to launch a new array of game-changing technologies on our successfully adopted platform. If you’re interested in working within a startup-oriented environment, while having the backing of a very large company, please read on.

Allergan Data Labs is a vibrant startup-minded organization with the backing of a large company. As a Senior Machine Learning Engineer, you will be responsible for collaborating with cross functional partners and applying your Machine Learning Engineering skills to deliver data-driven solutions for product teams, operations, marketing, and sales.

Responsibilities

• Architect and build robust cloud based systems to train, deploy, infer and monitor machine learning models and AI systems at scale

• Champion code quality, reusability, scalability, maintainability, and security, as well as provide input for strategic architecture decisions

• Integrate Machine Learning and AI systems with production applications using microservices architecture

• Set up model management system to measure the effectiveness of the models

• Collaborate with cross-functional partners (Product Managers, Data Scientists, Data Engineers, Software Engineers, Business teams) to build data products

• Implement processes and tools to ensure data quality, enforce data governance policies and engineering best practices

• Innovate with new approaches, staying abreast of current research and the latest technologies in the broader ML engineering community

Required Experience & Skills

• Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, Operations Research, or other quantitative field

• 5+ years of practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python, preferably …