Machine Learning Engineer II - Central ML
Role Description:
About Us:
At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.
Leadership/Team Quote:
The Content Intelligence team builds the Content Intelligence Platform by consuming millions of images and textual inputs every day, and then enriching it with ML capabilities. Eventually, these will serve downstream applications and personalize our customers' experience (think of a way to choose and surface the right images and reviews when customers book their next vacation).
Moreover the team is taking a key role in the new GenAI project - The AI Trip Planner.
Role Description:
You’ll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
- Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
- Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
- Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
- Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
- Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
- Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
- Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
Qualifications & Skills:
- Bachelor’s or master’s degree in computer science, Engineering, Statistics, or a related field.
- Minimum of 4 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.
- Strong programming skills in languages such as Python and Java.
- Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.
- Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
- Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.
- Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
- Deep understanding of machine learning algorithms, statistical models, and data structures.
- Experience in deploying large-scale language models like GPT, BERT, or similar architectures - an advantage.
- Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.
- Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.
- Experience of working on products that impact a large customer base - an advantage.
- Excellent communication in English; written and spoken.
Benefits & Perks - Global Impact, Personal Relevance:
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique-to-Booking.com benefits which include:
- Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave
- Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country)
- Industry leading product discounts
- up to 1400 per year
- for yourself, including automatic Genius Level 3 status and Booking.com wallet credit
Diversity, Equity and Inclusion (DEI) at Booking.com:
Diversity, Equity & Inclusion have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations.
Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone. Inclusion is at the heart of everything we do.It’s a place where you can make your mark and have a real impact in travel and tech.”
We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment.
Application Process:
This section should provide:
- Let’s go places together: How we Hire
- This role does not come with relocation assistance.
We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.