The Staff Research Scientist will be part of a talented Machine Learning (ML) group focused on developing innovative machine learning algorithms, scalable ML systems, and HBO Max applications.
As a Staff Research Scientist, you will focus on developing and deploying personalization and recommender systems, search, experimentation, audience, 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.
• Lead the full ML lifecycle.
• Maintain stakeholder relationships, engage with cross functional teams to drive project outcomes.
• Provide thought leadership for new projects and project directions.
• Collaborate with product owners, business leadership and engineering teams to translate business problems into scalable ML formulations.
• Apply or develop state of the art ML algorithms for the HBO Max applications.
• Integrate with A/B test platform to experiment with multiple model variants.
• Write robust production-level code and engage in code reviews.
• Work with ML engineers to deploy ML model pipelines, scale through Big Data, optimize performance.
• Incorporate ML best practices and influence their adoption into our machine learning infrastructure.
• Help keep the team up to date with advances in the domain.
• Help establish best practices for applied machine learning. Have strong ownership of functional excellence.
• Mentor less experienced team members and provide technical leadership.
• Technical education in Computer Science, Statistics, Physics, Mathematics, and other quantitative fields (Masters/Phd preferred).
• Has 5+ years of relevant hands-on experience in machine learning algorithm development and research with a track record of processing, enriching, and extracting value from large datasets.
• The candidate demonstrates strong problem-solving and interpersonal skills.
• Strong mathematical skills and familiarity with standard statistical methods including commonly used supervised and unsupervised ML techniques.
• Experience using advanced ML topics such as deep Learning, Bandits, Probabilistic Graphical Models, Reinforcement Learning, optimization algorithms preferred.
• Experience with recommender systems and information retrieval is strongly preferred.
• Familiarity with the following technologies and frameworks is 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
Jobcode: Reference SBJ-d89789-3-238-132-225-42 in your application.