About the job
***English version below***
Travel transcends destinations; it is woven from the memories created along the way. At Plusgrade, we are committed to redefining the future of travel by partnering with over 250 airlines, hotels, cruise lines, rail networks, and financial services to create meaningful new revenue streams through exceptional customer experiences. Grounded in our core values of ambition, innovation, and collaboration, we are continuously driven to push boundaries, exceed expectations, and harness the best of everyone. We cultivate a culture that believes our strength lies in our unity, working together to build an extraordinary future in the travel industry. Join us in transforming everyday journeys into truly remarkable experiences.
ABOUT THE POSITION
As a Machine Learning Engineer within the ML Applications team, you will be responsible for designing, developing, and deploying innovative machine learning platform solutions to tackle complex business challenges. This role requires a strong software development background, a keen interest in cutting-edge technologies, excellent problem-solving skills, and the ability to work both independently and collaboratively in a fast-paced environment.
This position reports to the Director of ML Applications.
YOUR RESPONSIBILITIES:
• Collaborate within a small team passionate about scaling the use of ML applications across the organization.
• Productionize, scale, and commercialize state-of-the-art machine learning solutions.
• Design and develop scalable and robust ML pipelines to enable predictive data usage by downstream applications, enhancing key performance indicators (KPIs) such as member engagement and revenue.
• Create and implement robust processes for monitoring production ML pipelines.
• Support production systems to deliver batch and real-time model predictions to all applications.
• Actively participate in solution design and modeling to ensure ML products are developed according to best practices, standards, and ML architecture principles.
• Work closely with our product, engineering, and marketing teams to develop data and ML solutions that address critical business questions.