Sr. Machine Learning Engineer

Irvine, CA; NYC, NY
Engineering
Full-Time

Allergan Data Labs is on a mission to transform the Allergan Aesthetics business at AbbVie, the fourth largest pharmaceutical company in the world. Allergan Aesthetics brands include Botox, CoolSculpting, Juvéderm and many more. The medical aesthetics business is ripe for disruption and we’re building a high performing product engineering team to do just that.

Our leadership has a fresh and innovative vision for how the company should approach digital marketing and product. We are utilizing machine learning in an effort to intelligently engage our customers in a more personalized and effective way. We’re looking for a strong Sr. Machine Learning Engineer who is interested in working within a startup-oriented environment while having the backing of a large company. You will deep dive into various data sources to identify insights that support Allergan Aesthetics business, design data pipelines in collaboration with data engineers, and team up with data scientists to identify new technologies and data infrastructures to improve maintainability and performance of the machine learning models.

Required Experience & Technical Skills

  • Solid understanding of end to end machine learning lifecycle
  • Proven track record of successful deployment of fully automated classification, regression, clustering or recommendation models at scale
  • Familiarity with popular machine/deep learning techniques such as boosting, bagging, Bayesian inferences, clustering, anomaly/outlier detection, recommender systems, recurrent neural network, and time-series forecasting
  • Professional experience with deploying and managing multiple production grade ETL pipelines at scale
  • Experience with writing enterprise level code to process, transport, analyze, and store data within SQL and NoSQL databases 
  • Expert level proficiency in Python
  • Proficiency in SQL
  • Experience with Docker, CI/CD pipelines, and Git version control
  • Experience with managing and architecting solutions on AWS or similar public clouds
  • Experience with building Batch and Streaming pipelines with Apache Spark is a plus
  • Good understanding of serverless technologies (such as AWS Lambda and Step functions or similar cloud providers) is a plus
  • Developing high performance API to expose data products is a plus
  • BS or MS in Computer Science or related field; or comparable experience/certifications

‍‍

Collaboration:

  • Must be collaborative and fun to work with, with good communication skills
  • Experience working with data scientists and data engineers
  • Coordinating and communicating with various stakeholders and partners including business and technical leaders
  • Participating in project management through capturing and developing tasks and stories, assisting in managing the backlog
  • Understanding of agile methodology
  • Mentoring junior team members

Core Values:

  • Be Humble: You’re smart yet always interested in learning from others.
  • Work Transparently: You always deal in an honest, direct and transparent way.
  • Take Ownership: You embrace responsibility and find joy in having the answers.
  • Learn More: Through blog posts, newsletters, podcasts, video tutorials and meetups you regularly self-educate and improve your skill set.
  • Show Gratitude: You show appreciation and return kindness to those you work with.

Perks

  • Competitive salary
  • Comprehensive medical, dental, vision and life insurance
  • 401k with up to 8% company match
  • Vacation / PTO
  • Entire week off for the holidays
  • Brand new MacBook Pro and accompanying equipment to do great work
  • Attend a tech conference of your choice each year
  • On-campus restaurant
  • On-campus gym, tennis court, basketball court and softball field
  • Discounts on Allergan products

The Allergan Data Labs team is led and comprised of technology and marketing experts with experience ranging from successful tech startups to large medical corporations. We welcome the interest and opportunity to speak with those from all backgrounds.