KAYAK seeks to improve user experience and enhance business outcomes through machine learning and AI, focusing on experimental projects and innovation across the business to distinguish their brand, delight users, and help customers experience the world with confidence.
Requirements
- Deep expertise in math, statistics, systems design, and coding sufficient to lead and solve complex industrial machine learning and data science challenges.
- Proven experience applying core concepts and methods in machine/deep learning to real-world data science problems, with a strong track record of measuring and influencing impact at scale.
- Proficient with current Python machine learning development ecosystems: PyTorch or TensorFlow, pandas/polars, scikit-learn, git, etc.
- Solid foundation in software engineering principles, with experience leading or mentoring in individual or team-based technical development.
- Demonstrated success applying ML/AI in a business environment, including shaping high-level business problems into concrete modeling tasks.
- Hands-on experience with data engineering practices, including ETLs, relational databases, and large-scale data frameworks such as Trino
- Prior experience with ML engineering and/or MLOps, including deploying, maintaining, and monitoring machine learning models in production environments.
Responsibilities
- Design and implement your own solutions to modeling problems to improve user experience and enhance business outcomes.
- Conduct experiments and engage in rapid-prototyping of ideas, making creative use of the data and resources at your disposal.
- Implement designs in a stable, maintainable, and scalable production-ready form.
- Extract, process and leverage large data sets to drive successful projects.
- Engage in group problem-solving, and collaborative team efforts.
- Communicate and share results in a clear and concise manner.
- Collaborate with strong researchers, product managers and engineers, and your work will have tangible impact
Other
- Note: This is a hybrid work role for candidates who can join at least 3 days per week in-office.
- A PhD or equivalent in an aligned quantitative field (computer science, statistics, mathematics, operations research, engineering, etc.) is preferred and is a strong indicator of preparation, though not strictly required: what you can do (or rapidly learn to do) is more important.
