As a Senior Machine Learning Scientist, you will be a strong technical leader within the team, setting the technical strategy, while generating operational business impact. You will be developing innovative Machine Learning models, being responsible for the design and delivery of ML systems, from initial idea-generation, collecting business requirements from product stakeholders to implementation. You will actively coach and mentor less experienced Machine Learning Scientists and Machine Learning Engineers in the team and work closely together with Data Engineers, Software Engineers and Product Managers.
Key Job Responsibilities and DutiesTranslate broad business problems into ML/AI challenges and develop a targeted research plan to identify the best approach within the constraints of the production environment.
Develop the technical strategy for machine learning on a product category by designing innovative ML/AI models, algorithms, and approaches that deliver both short-term commercial impact and longer-term differentiated business value and customer experiences.
Work in a multi-disciplined team where you’ll take full ownership of turning discoveries and ideas into products through machine learning (incl. understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment).
Define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.
Develop production-grade ML code for models, features, and pipelines, accounting for scalability, latency, realtime requirements, monitoring and retraining.
Build readable and reusable code, using the right technologies and coding methodologies applying knowledge of business area tools and product needs.
Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, introducing them to the machine learning community and promoting their application.
Promote platform-based development and reuse by coaching teams in abstracting individual business problems to generalized ML/AI products, rather than point solutions, and in identifying horizontal opportunities across multiple business domains.
Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI fields. Mentor others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.
Strong relevant academic and work experience (Master's degree + 8 years of working experience, or PhD + 6 years of working experience) in the development and application of Machine Learning.
Education in a quantitative field (e.g. Computer Science, Mathematics, Artificial Intelligence, Physics, etc.)
We prefer candidates with NLP experience, especially using LLMs.
Ability to craft an applied research plan for a product category from scratch as evidenced by peer-review publication or similar track record. Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Prior experience with Feature Engineering and putting machine learning models in production is a plus.
Strong working knowledge of Python, Hadoop, SQL, Spark or similar Big Data technologies.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, ML Engineers, Product Managers, etc.).
Excellent English communication skills, both written and verbal; the ability to convey your message to team members and other collaborators.
Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave
Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country)
A beautiful sustainable , that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office
Commuting allowance and bike reimbursement scheme
Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers
Free access to online learning platforms, development and mentorship programs
Global Employee Assistance Program, free Headspace membership
Bi-annual performance conversations, company-wide mentoring program, and internal development opportunities
Unlimited access to online learning platforms: Udemy, Coursera, LinkedIn learning, O'reilly
If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.
