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: Youโre 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)
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Allergan Data Labs
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