CWT is one of the world's leading digital travel management companies and as a Business-to-Business-for Employees (B2B4E) travel management platform, companies and governments rely on us to keep their people connected – anywhere, anytime, anyhow – and across six continents, we provide their employees with innovative technology and an efficient, safe and secure travel experience.

Our Technology division was formed to lead on our CWT 3.0 digital transformation strategy. With a team of highly skilled and experienced individuals, they deliver and manage efficient, quality, and innovative travel technology solutions and technology services for CWT and its customers worldwide

Position overview

We are looking for a Machine Learning Engineer to join our Data Science team at CWT. The MachineLearning Engineer will evolve the design and development of data and machine learning products tosupport business strategies, as well as ensuring that our machine learning services are scalable, reliableand robust.

The Machine Learning Engineer will work closely with other data and machine learning engineers, aswell as product owners and other teams within CWT to deliver solutions and insights for the business.

Daily Responsibilities

Working with the Data Science team to develop and deploy machine models into production forCWT’s travel booking systems across millions of travellers.Implementing Rest APIs and working with the wider Product Technology Department toensure end-to-end product delivery.Support the Data Science team in prototyping and delivering deep learning models forpersonalisation and new applications in the travel space.

#LI-Hybrid

#LI-SV

Skills and Experience

Proven experience in machine learning models, data pipelines and architectures.Experience designing and developing recommender system.Passionate about machine learning/deep learning algorithms (e.g. NLP).Experience implementing machine learning algorithms using Scala, SparkML, and Python.Experience with AWS (Serverless: Sagemaker, Lambda, API Gateway, EMR and related tools).Experience with implementing and integrating with Rest APIs.Experience delivering large scale projects where you applied machine learning theories andtechniques into Production systems.Working within Agile methodology

Desirable Skills

Experience implementing machine learning algorithms using TensorFlow.Experience using Anaconda Enterprise Data Science platform.Familiar with Test Driven Development.Experience with Amazon Lex.

Please note this is a hybrid position and the successful candidate will be required to working from our London office 2 days a week

CWT is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.

Skills and Experience

Proven experience in machine learning models, data pipelines and architectures.Experience designing and developing recommender system.Passionate about machine learning/deep learning algorithms (e.g. NLP).Experience implementing machine learning algorithms using Scala, SparkML, and Python.Experience with AWS (Serverless: Sagemaker, Lambda, API Gateway, EMR and related tools).Experience with implementing and integrating with Rest APIs.Experience delivering large scale projects where you applied machine learning theories andtechniques into Production systems.Working within Agile methodology

Desirable Skills

Experience implementing machine learning algorithms using TensorFlow.Experience using Anaconda Enterprise Data Science platform.Familiar with Test Driven Development.Experience with Amazon Lex.

Please note this is a hybrid position and the successful candidate will be required to working from our London office 2 days a week

CWT is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.