Travel is not just about the destination; it's about every memory made along the way. We are dedicated to shaping the future of travel by partnering with 250+ airline, hospitality, cruise, passenger rail, and financial services companies to create new, meaningful revenue streams through incredible customer experiences. Rooted in our core values of being ambitious, innovative, and collaborative, we are driven to continuously raise the bar, exceed expectations, and bring out the best in everyone, fostering a culture where we believe we are better together, working towards an extraordinary future in travel. Come help us transform everyday travel into extraordinary experiences.

As the ML Engineer for the ML Applications team, you will be responsible for designing, developing, and deploying innovative machine learning platform solutions to solve challenging business problems. This role requires a strong foundation in software development, a passion for cutting-edge technology, excellent problem-solving skills, and the ability to work independently and collaboratively within a fast-paced environment.

This role reports to the Director, ML Applications.

• Work in a small team passionate about enabling ML applications throughout the organization.

• Productionize, scale, and productize cutting-edge machine learning solutions.

• Design and develop scalable and robust ML pipelines for predictive data to be consumed by downstream applications to improve the main KPIs, such as member engagement, revenue, and others.

• Design and develop robust processes to monitor production ML pipelines.

• Support production systems to deliver batch and streaming 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 architectural principles.

• Work closely with our Product, Engineering, and Marketing teams to build the data and ML solutions to address business-critical questions.

• Deploy models and evaluate their performance; constantly test and improve.

• Responsible for model retraining, drift monitoring, pipeline automation, quality control, and governance of production models.

• Work closely with the OPS team to provide the necessary production support.

• 4+ years work experience with ML pipelines and ML-based Python development.

• Strong knowledge of general software engineering principles and practices.

• Expertise with RESTful APIs.

• Experienced building ML- and LLM-based recommendation systems.

• Experience designing and developing back-end components for low-latency and highly-scalable solutions.

• Working knowledge of ML Ops principles and CI/CD.

• Experience managing the machine learning algorithm lifecycle.

• Knowledge of ML-based application design principles.

• Experience with containers and related infrastructures, such as Docker and Kubernetes.

• Familiarity with native AWS tools.

• Strong optimization and debugging skills.

• Self-disciplined, motivated, eager to help, and most importantly, a thirst for continual learning.

• Effective communicator and collaborator, both within the immediate team and across other organizational units.

• Team spirit and a problem-solver mindset.

• Knowledge of data science principles.

• Experience with prompt engineering, retrieval-augmented generation (RAG), and vector databases

• AWS Architect certification. 

• Experience with web application development and UI/UX optimization.

• Experience with the design, implementation, and deployment of machine learning algorithms.

• Experience with relational databases and in-memory storage.

• Languages: Python, SQL, Spark, PySpark

• Tools: Snowflake, SnowPark, Splunk

• AWS Services: EKS, SageMaker, Bedrock, DynamoDB, Kinesis, RedShift, Lambda and others

• Containerization: Kubernetes, Docker

• Version Control: GitLab

• Data & Analytics: Dataiku, Tableau