Lead Machine Learning Engineer

March 1

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Allergan Data Labs

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Allergan Data Labs is on a mission to transform the medical aesthetics business at Allergan Aesthetics, an AbbVie company (NYSE: ABBV), one of the largest pharmaceutical companies in the world$1. .$1

201 - 500

Description

• As a Lead 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. • Take ownership for achieving objectives and key results for your team, allocate resources, oversee & own technical solutions, communicate schedule, status, and milestones • Lead and manage a small team of Machine Learning Engineers by setting goals, supervising work, providing guidance, evaluating performance, removing barriers, cultivating career development, and promoting job satisfaction • Collaborate with cross functional partners (Product Managers, Data Scientists, Data Engineers, Software Engineers, Business teams) to build data products • Architect and build robust systems to train, deploy, run inference, and monitor machine learning and AI models at scale • Champion code quality, reusability, scalability, maintainability, and security as well as providing input for strategic architecture decisions • Implement processes and tools to ensure data quality, enforce data governance policies and engineering best practices • Integrate Machine Learning and AI systems with production applications • Innovate with new approaches, staying abreast of current research and latest technologies in the broader ML engineering community

Requirements

• Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, Operations Research, or other quantitative field • 7+ years of experience as an engineer specialized building Machine Learning systems • 2+ years of leading a team of Machine Learning Engineers in projects to deliver data solutions • 1+ year of experience as the reporting manager for a small number of individual contributors • 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 data warehouses (e.g., dimensional modeling), data lakes/Lakehouses, and other data architectures • Experience with orchestrating complex workflows and data pipelines using like Airflow or similar tools • Ability to load test deployed models at scale to understand performance breakpoints • Experience with Git, CI/CD pipelines, Docker, Kubernetes • Experience with architecting solutions on AWS or equivalent public cloud platforms • Experience with developing data APIs, Microservices and event driven systems to integrate ML systems • 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 • Strong interpersonal and verbal communication skills • Leadership experience and the ability to mentor and guide a team

Benefits

• We offer a comprehensive package of benefits including paid time off. (vacation, holidays, sick) • Medical/dental/vision insurance and 401(k) to eligible employees. • This job is eligible to participate in our short-term incentive programs. • This job is eligible to participate in our long-term incentive programs.