Senior Applied Machine Learning Scientist
KAYAK Labs seeks resourceful, agile data scientists with a strong interest in solving challenging machine learning problems across a range of domains and modalities, from recommender systems to reinforcement learning to vision to natural language processing. Good candidates will be well-versed in recent advances in machine learning and will be comfortable quickly testing and iterating on new ideas. Positions at different levels of seniority are available.
KAYAK Labs is a cross-cutting team focused on experimental projects and innovation across the business. Leveraging ML/AI, optimization, and our unique data assets, we aim for novel, impactful products and breakthrough improvements. We seek to distinguish our brand, to delight our users, and to help our customers experience the world with confidence and peace-of-mind.
As part of the Labs team, you’ll collaborate with strong researchers and engineers, and your work will have tangible impact. You will be challenged; you will have an opportunity to shape our business and, by extension, the wider travel industry. You will expand your competence and explore new technologies at the intersection of AI, data engineering, computation, and product delivery at scale.
Note: This is a hybrid work role seeking candidates who can join at least 3 days per week in-office.
In this role, you will:
- Design and execute your own solutions to modeling problems that will improve user experience, and optimize key metrics important to the business.
- 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.
Please apply if you are/have:
- Comfortable with math, statistics, systems design and coding to the extent necessary to tackle industrial machine learning and data science challenges. A PhD in an aligned quantitative field (computer science, statistics, mathematics, operations research, engineering, etc.), is preferred and is a good indicator of sufficient preparation, but is not strictly required: what you can do (or quickly learn to do) is more important.
- Exposure to a minimum introductory level treatment of the core concepts and methods in machine/deep learning, and experience with their application to real-world data science problems.
- Proficient with current Python machine learning development ecosystems: PyTorch or TensorFlow, pandas/polars, scikit-learn, git, etc.
- Exposure to software engineering, whether individual or team-based.
- Direct experience applying ML/AI in a business environment, and experience distilling high-level business challenges down to concrete modeling problems.
- Hands-on experience with data engineering principles and methods: ETLs, relational databases, large-scale data frameworks like (Py)Spark.
Benefits and Perks
- 4 weeks paid vacation
- Ability to work from almost anywhere
- Day off on your birthday
- Generous retirement plans
- Awesome health, dental and vision insurance plans
- Flexible Spending Accounts
- Headspace Subscription
- No Meeting Fridays
- Drinks, coffee, snacks, games etc.
- Weekly catered lunches
- Flexible hours
- Universal Paid Parental leave
Diversity and Inclusion
We aspire to have a workplace that reflects all of the diverse communities we serve. We know that when we have diverse teams we produce more creative ideas, products, and better outcomes for our team members. OpenTable/KAYAK is proud to be an Equal Opportunity Employer and we welcome and encourage candidates from all backgrounds and experiences to apply for roles on our team. Whoever you are, just be you.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job responsibilities, and to receive other benefits and privileges of employment. Please contact us to request accommodation.