ML Engineer
Description For ML Engineer
Warner Bros. Discovery is seeking a Machine Learning Engineer to join their innovative team focused on advancing AI-driven solutions in the media and entertainment industry. This role offers an exciting opportunity to work on cutting-edge projects that enhance user experiences and optimize business operations through AI innovation. As an ML Engineer, you'll be responsible for designing, developing, and deploying machine learning models that power personalized content recommendations, real-time data analysis, and content moderation. The position requires collaboration with cross-functional teams and expertise in various ML domains including deep learning, NLP, and computer vision. You'll work in a dynamic environment that values innovation and continuous learning, with access to state-of-the-art technologies and the opportunity to shape the future of entertainment through AI applications. The role combines technical expertise with creative problem-solving, offering a unique chance to impact how millions of users interact with entertainment content. Warner Bros. Discovery provides a supportive environment for career growth, thoughtfully curated benefits, and the opportunity to work with some of the most iconic brands in entertainment.
Responsibilities For ML Engineer
- Design, develop, and train machine learning models including deep learning, NLP, computer vision, and reinforcement learning
- Implement data pipelines for model training and evaluation
- Deploy and maintain machine learning models in production environments
- Develop monitoring and alerting systems for model performance
- Collaborate with data scientists and engineers to optimize data pipelines
- Document ML workflows and contribute to building reusable ML tools
- Stay updated with AI/ML advancements and incorporate them into projects
Requirements For ML Engineer
- Bachelor's or Master's in Computer Science, Data Science, or related field
- 2+ years of experience in developing and deploying ML models in production
- Strong programming skills in Python with TensorFlow, PyTorch, and scikit-learn
- Proficiency in SQL and big data tools (Spark, Hadoop)
- Experience with cloud platforms (AWS, Azure, or GCP)
- Knowledge of Docker and Kubernetes
- Strong understanding of machine learning algorithms and techniques
- Excellent problem-solving, analytical, and communication skills
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