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EWS Sales Support Officer; UAE National | UAE

Job in Dubai, UAE/Dubai
Listing for: HSBC
Full Time position
Listed on 2026-02-06
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: EWS Sales Support Officer (UAE National role) | UAE
Machine Learning Engineer II - Performance Marketing

Machine Learning Engineer II - Performance Marketing

HSBC Amsterdam, Netherlands Apply now Posted 11 hours ago Permanent Competitive

Machine Learning Engineer II - Performance Marketing

About us: At , 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.

About the team: The Performance Marketing team builds and optimizes large-scale ML systems for online bidding across all major search providers, owning one of the industry's largest online advertising optimization platforms to keep  competitive. We run end-to-end research-to-production cycles-from POC models to production A/B tests-driving measurable impact by innovating in online auctions at scale.

Role Description: As a Machine Learning Engineer at , you will play a key role in shaping how millions of travelers experience our products. You'll work closely with ML scientists, software engineers, and product managers to turn business challenges into scalable, reliable ML solutions. Beyond delivery, you'll also contribute to applied research and reusable frameworks, ensuring  remains at the forefront of AI innovation.

Key Job Responsibilities and Duties

  • Develop production-grade ML systems, from models to features and pipelines, accounting for reliability, scalability, real-time requirements, monitoring and retraining.
  • Build readable and reusable code, applying code quality best practices and using standard libraries. Choose the right technology or coding methodology as well as refactor and simplify code when necessary.
  • Take full ownership of your services end to end by actively monitoring the systems health, performance and business impact.
  • Be responsible for business related data governance processes, the technical implementation and maintenance of data processing services and storage systems, and the implementation and maintenance of ML governance processes.
  • Evaluate possible architecture solutions taking into account the business and technology requirements.
  • Set the relevant service level objectives SLOs and act accordingly when they are not met.
  • 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 and upskilling on these, as needed.
  • Contribute to the internal ML/AI community by sharing your knowledge and participating in our internal ML programs.
  • Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
  • Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of disciplines and related fields.
  • Achieve mutually agreeable solutions by staying adaptable, communicating ideas in clear coherent language and practising active listening
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 GCP/AWS for training, evaluation and serving ML models using Tensor Flow, PyTorch, or scikit-learn.
  • Experience with big data processing frameworks such, Big Query, PySpark, Snowflake or similar frameworks.
  • Deep understanding of machine learning algorithms, statistical models, and data structures.
  • Experience in deploying and inference for large-scale machine learning models - an advantage.
  • Proficiency in data manipulation, analysis, and visualization using tools like Num Py, pandas, and matplotlib - an advantage.
  • Experience…
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