Welcome to Warner Bros. Discovery... the stuff dreams are made of.
Who We Are...
When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what's next...
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
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Your New Role:
As a Machine Learning Engineer at Warner Bros Discovery, you will be part of a dynamic team driving the next generation of AI innovation in the media and entertainment industry. Our company is at the forefront of digital transformation, leveraging cutting-edge technologies to redefine content creation, distribution, and consumption. In this role, you will design, develop, and deploy machine learning models that enhance user experiences, optimize business operations, and unlock new possibilities in the entertainment space.
Your expertise will play a critical role in advancing AI-driven solutions that power personalized content recommendations, real-time data analysis, content moderation, and more. You will collaborate with data scientists, software engineers, and other cross-functional teams to deliver impactful machine learning solutions at scale, shaping the future of the entertainment industry.
This is an exciting opportunity for a highly skilled Machine Learning Engineer to join a forward-thinking organization and work on some of the most innovative AI projects in the world.
Your Role Accountabilities:
1. Machine Learning Model Development
- Design, develop, and train a variety of machine learning models, including deep learning, natural language processing, computer vision, and reinforcement learning.
- Conduct thorough experimentation and analysis to optimize model performance, accuracy, and efficiency.
- Implement robust data pipelines for model training and evaluation, ensuring data quality and consistency.
- Stay abreast of the latest research and advancements in machine learning and apply them to solve challenging problems.
- Collaborate with data scientists and researchers to translate research findings into production-ready solutions.
2. Data Processing and Engineering
- Work closely with data engineers to design and implement data pipelines for feature engineering, data transformation, and model training.
- Ensure data quality and consistency across the entire machine learning lifecycle.
- Develop and maintain data pipelines for model training and evaluation, ensuring data quality and consistency.
- Explore and implement innovative data management techniques to improve model performance and efficiency.
- Collaborate with data scientists and engineers to optimize data pipelines for machine learning workloads.
3. Model Deployment and Monitoring
- Deploy and maintain machine learning models in production environments, ensuring scalability, reliability, and performance.
- Develop and implement monitoring and alerting systems to track model performance, identify anomalies, and proactively address issues.
- Continuously evaluate and improve deployed models, ensuring they remain effective and meet evolving business needs.
- Optimize model performance in production environments, addressing latency, resource utilization, and cost-effectiveness.
4. Collaboration and Documentation
- Partner with data scientists, software engineers, and product teams to translate business problems into ML solutions.
- Document ML workflows, decisions, and key insights to foster team learning and knowledge sharing.
- Contribute to building reusable ML tools and frameworks.
5. Innovation and Learning
- Stay updated with advancements in AI/ML and incorporate them into ongoing projects.
- Participate in hackathons, internal competitions, and knowledge-sharing sessions.
Qualifications & Experiences:
- Bachelor's or Master's in Computer Science, Data Science, or a related field.
- 2+ years of experience in developing and deploying ML models in production environments.
- Strong programming skills in Python and experience with libraries like TensorFlow, PyTorch, and scikit-learn.
- Proficiency in SQL and big data tools (e.g., Spark, Hadoop).
- Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker and Kubernetes.
- Strong understanding of machine learning algorithms and techniques, including deep learning, natural language processing, and computer vision.
- Excellent problem-solving, analytical, and communication skills.
- Passion for innovation and a strong desire to learn and grow.
How We Get Things Done...
This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.
Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects the diversity of our society and the world around us. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.
If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.