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Lead Machine Learning Engineer
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Lead Machine Learning Engineer
- San Diego, California, United States
- San Diego, California, United States
Über
About AbbVie At Allergan Aesthetics, an AbbVie company, we develop, manufacture, and market a portfolio of leading aesthetics brands and products. Our aesthetics portfolio includes facial injectables, body contouring, plastics, skin care, and more. Our goal is to consistently provide our customers with innovation, education, exceptional service, and a commitment to excellence, all with a personal touch. For more information, visit https://global.allerganaesthetics.com/. Follow Allergan Aesthetics on LinkedIn. Job Description
Responsibilities: Collaborate with cross-functional partners (Product Managers,DataScientists,DataEngineers, SoftwareEngineers, Business teams) to builddataand Machine Learning products Take ownership of objectives and key results for your workstream, and own technical solutions in partnership with your manager Architect and build robust systems to train, deploy, run inference, and monitor Machine Learning and AI systems at scale Champion code quality, reusability, scalability, maintainability, and security, and provide input into strategic architecture decisions Implement processes and tools to ensuredataquality, enforcedatagovernance policies andengineering 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 MLengineering community Qualifications
Required Experience & Skills: Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics,DataScience,Engineering, Operations Research, or other quantitative field 7+ years of experience as anengineerspecialized building Machine Learning systems 2+ years of technicalleadership delivering machine learning solutions in partnership withengineers, scientists, and business stakeholders 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,datadrift detection, etc. Experience with building batch and streaming pipelines using complex SQL, PySpark, Pandas, and similar frameworks Experience withdatawarehouses (e.g., dimensional modeling),datalakes/Lakehouses, and otherdataarchitectures Experience orchestrating complex workflows anddatapipelines using Airflow or similar tools Ability to load test deployed models at scale to identify performance bottlenecks Experience with Git, CI/CD pipelines, Docker, Kubernetes Experience with architecting solutions on AWS or equivalent public cloud platforms Experience with developingdataAPIs, 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 newdatatools to enhance the machine learning stack Strong interpersonal and verbal communication skills Technicalleadership experience and the ability to mentor and guide others Preferred Experience & Skills: Knowledge ofdatamesh concepts Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science Knowledge of vectordatabases, knowledge graphs, and other approaches for organizing & storing information Familiarity with Snowflake, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, Sagemaker,DataDog, PagerDuty,DataCataloging tools,DataObservability tools andDataGovernance tools
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law: The compensation range described below is the range of possible base pay compensation that the Companybelieves ingood faith it will pay for this role at the timeof thisposting based on the job grade for this position.Individualcompensation paid within this range will depend on many factors including geographic location,andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture.
We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligibleemployees.
This job is eligible toparticipatein our long-term incentiveprograms.
Note: No amount of payis considered to bewages or compensation until such amount is earned, vested, anddeterminable.The amount and availability of any bonus, commission,incentive, benefits, or any other form ofcompensation and benefitsthat are allocable to a particular employeeremainsin the Company's sole andabsolutediscretion unless anduntil paid andmay bemodifiedat the Company’s sole and absolute discretion, consistent withapplicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.
Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: https://www.abbvie.com/join -us/reasonable- accommodations.html
Sprachkenntnisse
- English
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