Senior Machine Learning Engineer

1 month ago

Irvine, United States Allergan Data Labs Full time

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)

#J-18808-Ljbffr

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