Your New Role:

- As the Director ML Engineering & Automation, you will lead a dynamic team at the forefront of transforming the Media & Entertainment industry.

- In this high-impact role, you will be responsible for driving the strategic direction and execution of ML and AI solutions to enhance content personalization, automate workflows, and provide innovative, data-driven experiences.

- You will work closely with cross-functional teams, including Data Scientists, Software Engineers, and Product Managers, to deliver cutting-edge solutions that fuel business growth and deliver the next generation of entertainment experiences.

- This is an exciting opportunity to shape the future of entertainment through AI-driven innovation.

- In this leadership role, you will have the opportunity to build and scale a world-class ML engineering team, while leveraging your expertise to solve some of the most complex and exciting challenges in the industry.

- This role combines technical excellence, strategic vision, and team leadership to make a lasting impact on the company's mission.

Your Role Accountabilities:

Leadership & Team Building:

- Lead, mentor, and grow a high-performing ML engineering team, fostering a culture of innovation and continuous improvement.

- Define and execute the roadmap for building scalable, high-impact ML solutions that support the company's core business and strategic objectives.

- Collaborate closely with leadership across departments, including data science, product management, and IT, to ensure alignment of ML initiatives with business needs.

- Establish clear performance metrics and regularly assess the effectiveness of the team and individual contributors.

- Promote knowledge-sharing, best practices, and a growth mindset within the team to enhance technical depth and execution efficiency.

End-to-End ML Solution Development:

- Oversee the design, development, deployment, and maintenance of machine learning models and systems that power content recommendation engines, personalization, automation, and other key business areas.

- Drive the adoption of best practices in model development, testing, monitoring, and optimization across the team.

- Build scalable, production-ready ML pipelines that process vast amounts of data and generate real-time insights.

- Ensure that solutions are optimized for performance, cost-efficiency, and maintainability in a cloud-native, microservices environment.

- Lead efforts to continuously improve model performance, incorporating user feedback and business metrics.

Innovation & Strategy:

- Identify and evaluate emerging technologies, algorithms, and methodologies in the AI/ML space, integrating them into the company's tech stack to maintain a competitive edge.

- Work closely with senior leadership to define AI/ML strategies and influence decision-making on product and business development.

- Evaluate and implement advanced techniques in natural language processing (NLP), computer vision, deep learning, reinforcement learning, and other domains as relevant to the media industry.

- Provide thought leadership on the application of AI/ML in media and entertainment, positioning the company as a leader in AI-driven innovation.

Collaboration & Cross-Functional Engagement:

- Partner with product management, engineering, and business teams to translate complex business problems into technical ML solutions.

- Collaborate on the integration of ML models into products and workflows, ensuring smooth end-to-end delivery from prototype to production.

- Act as a trusted advisor to executives and stakeholders on ML capabilities, project status, risks, and business impact.

- Drive the development and implementation of data governance, privacy, and security practices to ensure compliance with regulatory requirements.

- Facilitate the sharing of ML insights with broader company teams, providing transparency and fostering a data-driven culture.

Performance Monitoring & Reporting:

- Define and track key performance indicators (KPIs) to measure the success of ML initiatives and models.

- Oversee the collection and analysis of model performance data, providing regular updates to leadership and stakeholders.

- Ensure that deployed models are continuously monitored, maintained, and updated to meet evolving business needs.

- Lead post-mortem analyses of model failures and actively drive improvements based on lessons learned.

- Utilize data to iterate and refine models to increase their accuracy and efficiency.

Qualifications & Experiences:

- Master's or Ph.degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field from a reputed institution.

- 12+ years of experience in the field of machine learning and AI, with at least 5 years in a leadership or managerial role.

- Proven track record of successfully leading and scaling ML engineering teams and delivering large-scale ML projects in a fast-paced environment.

- Experience working in the Media & Entertainment industry or related sectors, with knowledge of data-driven content recommendations, personalization, and automation.

- Expertise in designing, building, and deploying production-grade machine learning systems at scale.

- Experience in leading cross-functional teams to deliver end-to-end machine learning solutions, from conceptualization to deployment and optimization.

- Demonstrated ability to influence senior stakeholders and executives, translating technical concepts into business impact.

- Strong expertise in machine learning algorithms, deep learning, reinforcement learning, and statistical modeling techniques.

- In-depth knowledge of data structures, software engineering principles, and system design.

- Experience with distributed computing and cloud technologies (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

- Proficiency in programming languages such as Python, Java, or Scala, and familiarity with ML frameworks like TensorFlow, PyTorch, or Keras