Senior Machine Learning Engineer

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 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

• Strong interpersonal and verbal communication skills

Preferred Experiences & Skills

• 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

• Familiarity with Snowflake, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, Sagemaker, DataDog, PagerDuty, Atlan, Data Observability tools and Data Governance tools

Our 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.
• 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 SkinMedica skin care products.
• Discounted aesthetic treatment days multiple times a year.
• $600 worth of Alle benefits each year to use towards aesthetic treatments and products.
• Eligible for donation matching to over 1.5 million nonprofit organizations.
• Attend AWS Re:Invent in person (Las Vegas) or virtually each year (for certain roles)