Machine Learning Engineer

4 weeks ago


Mettawa, Illinois, United States AbbVie Full time

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas immunology, oncology, neuroscience, and eye care and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us Follow @abbvie onTwitter,Facebook,Instagram,YouTubeandLinkedIn.
Job Description

Are you ready to shape the future of machine learning operations? Do you have a passion for building and optimizing machine learning pipelines at a scale? Do you thrive in a fast-paced environment, where your skills can drive real-world business outcomes? If so, we have an exciting opportunity for you.

The Winning with Data (WWD) capability in AbbVies International Commercial Business is driving the transformation of the organization into a data driven decision-making organization and is seeking an experienced and talented Machine Learning Operations Engineer to join our team.

In this role, you will be responsible for implementing scalable and efficient processes for deploying machine learning models into production environments and will play a pivotal role in shaping our machine learning deployment processes. The role bridges the gap between data science and IT operations, ensuring that machine learning models are seamlessly integrated into our production systems.

In this role you will be responsible for:

Model Deployment: Participate efforts to deploy machine learning models into production environments, making them available for real-time inference and ensuring scalability and reliability.Collaboration: Collaborate with data scientists, software engineers, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.Continuous Integration/Continuous Deployment (CI/CD): Implement and optimize CI/CD pipelines for machine learning models, automating testing and deployment processes.Monitoring and Logging: Set up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance.Version Control: Implement version control systems for machine learning models and associated code to track changes and facilitate collaboration.Research and Evaluate: Research and evaluate emerging technologies and tools to enhance machine learning operations and efficiency.Security and Compliance: Ensure that machine learning systems meet security and compliance standards, including data protection and privacy regulations.Documentation: Maintain clear and comprehensive documentation of ML Ops processes and configurations.Tools and skills you will use in this role :Palantir Foundry (or similar platforms such as databricks)Pyspark, Python, SQL, TypeScriptMachine Learning Packages (Scikit-learn, Tensorflow, PyTorch, Keras, Numpy)Git, Jira, Confluence, JenkinsAWS
Qualifications
Experiences that make you a strong candidate for this role:

Required:

Bachelors Degree with 6 years experience; master's degree with 5 years experience; PhD with 0 years experience.2+ years of experience as a Machine Learning Ops Engineer or in a similar roleStrong programming skills in Python, SQL, PySpark, TypeScript, library and packages related to data manipulation, statistical analysis, chart/plot, and machine learning algorithms and framework.Proficiency in PySpark dataframe and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries.Strong experience with Machine Learning life cycle, be able to implement feature store, MLflow, model registry, model deployment, model serving, model monitoringProficiency in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classificationExperience in analyzing time-series data for forecasting and trend analysis such as prescription forecastingExperience with Pharmaceutical industry, commercial operations Beneficial: Proficiency in containerization technologies (e.g., Docker, Kubernetes).Experience with Veeva CRM, SAP or Palantir FoundryExperience in large scale AI problems, ideally in the generative-AI field.Strong high-level programming skills (e.g., Python), frameworks and tools such as Pytorch lightning, kuberflow, TensorFlow, transformers, etc. This role has the potential to be remote.
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 ingood faith it will pay for this role at the time of this posting based on the job grade for this position. Individualcompensation paid within this range will depend on many factors including geographic location, and we may ultimatelypay 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/visioninsurance and 401(k) to eligible employees. This job is eligible to participate in our short-term incentive programs. Note: No amount of payis considered to bewages or compensation until such amount is earned, vested, and determinable.The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefitsthat are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid andmay be modified at the Companys sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion. It is AbbVies policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status. US & Puerto Rico only - to learn more, visit

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