Machine Learning Engineer II - GenAI
Role details
Job location
Tech stack
Job description
- 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.
Requirements
- 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 & conditions
Benefits & Perks - Global Impact, Personal Relevance:
- 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.
"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."