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Lead Machine Learning EngineerAbbVie • United States
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Lead Machine Learning Engineer

AbbVie
  • US
    United States
  • US
    United States
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À propos

Job Title
Machine Learning Engineer 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. Job Description
Responsibilities: Collaborate with cross-functional partners to build data and 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 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 Qualifications
Required Experience & Skills: 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 technical leadership delivering machine learning solutions in partnership with engineers, 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, 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 orchestrating complex workflows and data pipelines 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 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 Technical leadership experience and the ability to mentor and guide others Preferred Experience & Skills: Knowledge of data mesh concepts Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science Knowledge of vector databases, 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, Data Observability tools and Data Governance tools Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. 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 long-term incentive programs. 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 Recruitment Fraud Alert We have recently become aware of various recruitment phishing scams targeting job seekers. Please be advised: AbbVie will never request sensitive personal information (such as bank account details, social security numbers, or payment of any kind) during the recruitment process. If you suspect you have received a fraudulent offer or communication claiming to be from AbbVie, please do not respond, open any attachments, or click on any hyperlinks. If you have any questions or concerns regarding the authenticity of a communication alleged to have been made by or on behalf of AbbVie, please contact us immediately. Protect yourself by verifying job offers and communications. Your safety is important to us. Pay Range: $124500 - 236500 USD Where We Work
Role is not performed at a site or office and requires limited or no travel to a site or office.
  • United States

Compétences linguistiques

  • English
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