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Staff Solutions Architect - AI/ML

  • Source: Wbd
  • Warner Bros. Discovery
  • On-site
  • State of Telangāna, India
  • Mid level

Job Description

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.

Your New Role:

As the Staff, Solutions Architect (AI/ML), you will play a pivotal role in driving the adoption of AI and Machine Learning solutions within one of the world’s largest Media & Entertainment companies. Based in India, you will lead the design and implementation of innovative AI/ML architectures that transform how we create, distribute, and monetize content across global markets.

Your expertise will help bridge the gap between complex business challenges and advanced technical solutions, ensuring AI initiatives deliver real business value. This is a unique opportunity to work at the intersection of creativity and technology, where you’ll lead the development of intelligent solutions for personalized viewer experiences, optimized content workflows, and data-driven decision-making.

If you’re passionate about leveraging AI/ML to revolutionize the Media & Entertainment industry and thrive in a dynamic, collaborative environment, this role is for you.

1. AI/ML Solution Design and Development

  • Design and develop scalable AI/ML solutions tailored to address business challenges such as audience analytics, content personalization, and ad optimization.
  • Lead the end-to-end architecture of AI/ML platforms, ensuring seamless integration with existing systems and data pipelines.
  • Collaborate with data scientists, engineers, and business stakeholders to convert models into production-ready solutions.
  • Evaluate and select appropriate AI/ML frameworks, technologies, and tools to meet project requirements.
  • Ensure AI solutions are optimized for performance, scalability, and reliability across diverse use cases.

2. Technical Leadership and Innovation

  • Provide technical leadership for AI/ML projects, guiding teams through solution architecture, development, and deployment.
  • Stay abreast of emerging AI/ML trends and technologies to introduce innovative solutions and best practices.
  • Lead proof-of-concept (POC) initiatives to validate new AI capabilities and demonstrate their potential impact.
  • Promote a culture of innovation within the team, encouraging experimentation with cutting-edge AI/ML techniques.
  • Mentor junior architects and engineers to build a strong pipeline of AI/ML talent.

3. Collaboration and Stakeholder Engagement

  • Act as a key interface between business units, technical teams, and senior leadership to align AI/ML solutions with organizational goals.
  • Translate business requirements into technical specifications, ensuring clarity and feasibility.
  • Collaborate with cross-functional teams to prioritize and execute AI/ML projects that deliver the highest business impact.
  • Communicate the value and progress of AI/ML initiatives to non-technical stakeholders through clear, compelling narratives.
  • Foster strong relationships with external partners, including technology vendors and academic institutions, to drive innovation.

4. AI Governance and Risk Management

  • Implement best practices for AI/ML governance, including model explainability, accountability, and ethical use.
  • Ensure AI solutions comply with data privacy regulations and internal security protocols.
  • Proactively identify and mitigate risks associated with AI/ML implementations, such as bias, overfitting, or data quality issues.
  • Develop monitoring frameworks to track model performance and retrain models as necessary to maintain effectiveness.
  • Establish guidelines and documentation for AI/ML processes, ensuring consistency and transparency.

5. Scalability and Continuous Improvement

  • Architect solutions that are modular and scalable, capable of supporting future business growth and technological evolution.
  • Regularly review and optimize existing AI/ML systems for i…

Skills

  • curated
  • streamline
  • google-cloud-platform
  • amazon-web-services
  • amazon-machine-learning
  • Tensorflow
  • PyTorch
  • Scikit-learn
  • microsoft-azure
  • Python
  • Java
  • Spark
  • Hadoop
  • apache-hadoop
  • Tableau
  • power-bi
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