As a Machine Learning Engineer, you will be part of a talented Machine Learning (ML) group focused on developing innovative machine learning algorithms, scalable ML systems, and HBO Max applications.
You will focus on developing and deploying engineering systems such as customer life cycle models, audience segmentation systems, personalization and recommender systems, search, experimentation, and content AI solutions to drive user experience and growth.
You will partner closely with product, engineering, content, marketing, and research stakeholders across WarnerMedia to identify ML opportunities, accelerate AI innovation, and ensure the delivery of impactful solutions for the business.
• Work with data scientists, data engineers to design best-suited, robust, and scalable ML solutions and evaluate the deployed ML model's effectiveness.
• Write robust production-level and well tested code and engage in code reviews.
• Deploy ML model pipelines, scale through Big Data, optimize performance and automate fail-over.
• Enhance our machine learning infrastructure and framework.
• Collaborate with other MLE teams to promote and contribute to shared services and libraries.
• Design and implement data pipelines and data quality controls.
• Raise the bar on SDLC and CI/CD practices.
• Technical education in Computer Science, Information Science, Engineering, or equivalent experience (Masters degree or higher preferred).
• Has relevant and hands-on experience in Machine Learning Engineering with a track record of building high quality, scalable and robust ML solutions. We will consider exceptional entry level candidates, Industry experience preferred.
• Has experience in incrementally building big data product and production pipelines to support product functionalities, data and analytic functions.
• Flexible and comfortable working in a dynamic team environment with a distributed organization and minimal process.
• Familiarity with the following technologies and frameworks is strongly preferred:
• ML Technologies: Spark, MxNet, TensorFlow, Scikit-Learn
• AWS stack with a specific focus on the following solutions: EMR, Glue, Sagemaker, ECS/EKS, Lambda, CloudWatch
• Data stack: Snowflake, Grafana, SQS/Kafka/Kinesis
• Proficient in Python and OOP languages like Java
• ML model pipelines, orchestration frameworks, micro-services architecture
• Familiarity with data science techniques is a plus.
Jobcode: Reference SBJ-gq5v5m-3-227-235-216-42 in your application.