Machine Learning Manager - Ranking Team

The Ranking team is powering the ordering of products across various touchpoints on the platform, with a primary focus on optimizing search results. The team manages billions of requests daily, each of which relies on cutting-edge Machine Learning (ML) solutions to allow customers to experience the world.
Role Description:
As the Machine Learning Manager, you will manage a team of ML scientists & engineers, Data scientists & engineers which all work on different aspects for ranking/recommendation of products.
You will lead & own all related technical aspects of the ML based solution and collaborate with additional stakeholders (Engineering & Product) for providing the best outcome for our customers.
As a technical manager, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.

As the ML manager of the team, you are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.

Key Job Responsibilities and Duties:
Build a strong team within their area, by coaching and developing individual contributors
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business. Design and execute applied research plans to understand, apply, test, evolve, and generalise these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments.
Make things happen by maintaining motivation and conveying a sense of urgency, focusing on outcomes and accomplishments, while respecting the need to balance long- and short-term goals, by applying influencing techniques and decision making skills.
Drive, coach and mentor others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
Continuously evolve your craft. Keep up to date with industry and academic standard methodologies, periodically explore new technologies, introduce them to the machine learning community and promote their application in areas where they can generate impact.
Actively contribute to Machine Learning at through training, exploration of new technologies, interviewing.