Allergan Data Labs is hiring a
Senior Machine Learning Engineer

Summary

The job is for a Senior Machine Learning Engineer at Allergan Data Labs, a vibrant startup-oriented organization within AbbVie. The role involves collaborating with cross-functional partners to build data products, architect and build cloud-based systems, and apply machine learning engineering skills to various teams.

Requirements

• 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 within the AWS ecosystem
• Strong programming skills in Python and understanding of core computer science principles
• Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc
• Ability to design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc
• Experience with MLOps practices such as automated model deployment, model performance monitoring, data drift detection, etc
• Experience with building batch and streaming pipelines using complex SQL, PySpark, Pandas, and similar frameworks
• Experience with orchestrating complex workflows and data pipelines using like Airflow or similar tools
• Experience with architecting solutions on AWS or equivalent public cloud platforms
• Experience with Git, CI/CD pipelines, Docker, Kubernetes
• Experience with developing data APIs, Microservices and event driven systems to integrate ML systems
• Ability to load test deployed models at scale to understand performance breakpoints
• Familiarity with Large Language Models (LLMs), other generative AI modalities, and how they are applied in production
• Experience in assessing and implementing new data tools to enhance the machine learning stack

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

Preferred Qualifications

• Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science
• Knowledge of data mesh concepts
• Experience with managing and architecting solutions on AWS

Benefits

• Competitive salary
• Competitive annual bonus targets
• 401k with dollar for dollar match, up to 6% of eligible earnings (base, bonus). Plus additional company contribution
• RSU grants (Long Term Incentives) for approved roles
• Comprehensive medical, dental, vision and life insurance
• 17 paid holidays per year, including 3 floating holidays
• Annual Paid Time Off (PTO), with separate sick days
• 12 weeks paid Parental Leave
• Caregiver Leave
• Adoption and Surrogacy Assistance Plan
• Flexible workplace accommodations
• We celebrate our wins with opportunities to attend Lakers, Knicks, Anaheim Ducks, Anaheim Angels and NY Rangers games
• Opportunities to attend concerts, festivals and other live entertainment events in recognition of delivering great work
• Tuition reimbursement
• Attend a tech or marketing conference of your choice each year
• A MacBook Pro and accompanying hardware to do great work
• A modern productivity toolset to get work done: Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more
• Generous discounts on AbbVie products
• Discounted gym membership