At Booking.com, we want to empower everyone to experience the world. Through our products, partners, and people are how we do it. There's a whole planet of possibilities out there, and we bring it all together, in one place. Booking.com (USA), Inc, one of the support companies in the United States, is seeking a full timeSenior Machine Learning Engineer role.
Role Description:
As a Senior Machine Learning Engineer you are a driver of your subject area, who generates significant business impact directly and indirectly, and crafts the direction of product initiatives by being driven and having full ownership of your projects - from conceptualization to collecting data, annotating, feature engineering, productionizing and training model pipelines, deploying experiments, measuring and iterating on them - as well as coaching other Machine Learning Engineers, Scientists, Data Engineers, Product Managers, etc to do the same.
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At Booking.com, data drives our decisions. To do it more efficiently we are building a platform for data scientists. Our Machine Learning Platform is behind what makes Booking able to deliver personal experiences and you will be a part of its development helping to support multiple areas of the business as they use ML to address some of the hardest problems that we face, from detecting fraud to recommending which properties you should check for your next stay.
Our Machine Learning Production team is responsible for developing and owning the infrastructure and services in charge of hosting hundreds of machine learning models and serving millions of predictions per second for the rest of the company with strict low latency constraints in a cost-effective manner.
What You'll Be Doing:
- Translate specific business problems into ML/AI challenges and identify the best approach within the constraints of the production environment. Build proof-of-concepts to test new insights and demonstrate their potential value to relevant partners.
- Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime inference, monitoring and retraining. Monitor product health, performance and business impact and act accordingly when not met.
- Build readable and reusable code, choosing the right technologies, coding methodologies, and approach from carefully designed rapid prototyping to software deployment at scale. Find opportunities for platform-based development and reuse by abstracting business problems to generalized ML/AI solutions.
- Implement applied research plans for machine intelligence on a specific product 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. Document and share the findings.
- Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI subject areas and related fields. Mentor others through evidence and clear communication, explaining sophisticated technical concepts.
- Identify underlying issues and opportunities across domains and situations through application of structured thinking and logic, and formulate possible improvements.
- 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 in areas where they can generate impact.
- Actively supply to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.
- Push for improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams.
- 5+ years of relevant work experience (or equivalent), involved with the application of Machine Learning to business problems in a commercial environment.
- Shown experience of multiple machine learning facets, such as working with large data sets, experimentation, scalability and optimization.
- You have experience working on low latency services, and can guarantee performance even when traffic scales to hundreds of thousands of requests per second; you can profile production applications to identify performance bottlenecks.
- Experience running Machine Learning systems in production is a must, with knowledge on how to generate predictions for ML frameworks with high throughput and low latency.
- Strong skills and working experience with at least two server-side programming languages; Java or Scala specific knowledge is an advantage.
- Experience with data-driven product development: analytics, A/B testing, etc.
- You have a 'can do' demeanor and you act proactively and not reactively.
- Bachelor or higher in Computer Science, Artificial Intelligence, Software Engineering, or related fields.
- Excellent English interpersonal skills, both written and verbal.
- You are required to live within a commutable distance from your assigned office location
Booking.com's Total Rewards Philosophy is not only about compensation but also about benefits. Our Total Rewards are aimed to make it easier for you to experience all that life has to offer on your terms, so you can focus on what really matters. We offer competitive compensation as well as thoughtful, valuable, and even fun benefits which include:
- Medical, life, and disability insurance
- Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, sick, and care leave
- Industry leading product discounts for yourself, friends, and family, including automatic Genius Level 3 status and quarterly Booking.com wallet credit
- Free access to online learning platforms, mentorship programs, and a complimentary Headspace membership
- Collaborative, friendly and diverse culture
- Referral Program
- This role will have a salary range of: $231,400 - $250,000
- Additional Annual or Quarterly bonus potential (role dependent)
- Please note that while our philosophy is the same in every location, benefits may differ by office/country.
Pre- Employment Screening:
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.