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dubizzle

Machine Learning Engineer

dubizzle
United Arab Emirates · Full-time · Mid-Senior

Bayut & dubizzle have the unique distinction of being iconic, homegrown brands with a strong presence across the seven emirates in the UAE. Connecting millions of users across the country, we are committed to delivering the best online search experience.

As part of Dubizzle Group, we are alongside some of the strongest classified brands in the market. With a collective strength of 8 brands, we have more than 160 million monthly users that trust in our dedication to providing them with the best platform for their needs.

As the Machine Learning Engineer, you will be participating in exciting projects covering the end-to-end Data Science lifecycle - from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development. You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments - such as product & tech, the core business verticals, trust & safety, finance and others - to enable them to be successful.

In this role, you will:

  •  Work on regression and classification problems on tabular, textual and image data
  •  Work on forecasting, anomaly detection and time-series analysis
  •  Build recommendation engines
  • Work on GPT-based applications using stock models for various business use cases
  •  Query large datasets in AWS Redshift to extract the necessary data that will feed ML models
  •  Perform data exploration to find patterns in the data and understand the state and quality of the data available
  •  Utilize Python code for analyzing data and building statistical models to solve specific business problems
  •  Evaluate ML models and fine tune model parameters considering the business problem behind
  •  Collaborate with senior peers to Deploy ML models into production that work as standalone data services
  •  Build customer-facing reporting tools to provide insights and metrics which track system performance
  •  Participate in the off-hours on call stability rota to support live ML models
  •  Own at least one ML product that is in production




Requirements

  • Master's degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field
  • 2+ years of working experience in Machine Learning
  • Experience with AWS is a plus
  • Knowledge in Statistical modelling and maths
  • Intermediate knowledge of Python's ML stack: Pandas, Matplotlib, Sklearn, Tensorflow
  • Intermediate knowledge of machine learning algorithms such as Linear regression, Gradient boosted trees, Neural networks
  • Basic knowledge of SQL, and visualization tools such as Periscope with experience in handling large datasets
  • Basic knowledge of statistical analysis and A/B testing
  • Excellent verbal and written communication
  • Strong problem solving skills
  • Analytical thinking; Conceptual thinking Detail-oriented; Business Acumen
  • Entrepreneurial spirit and ability to think creatively; highly-driven and self-motivated; strong curiosity and strive for continuous learning




Benefits

  • A fast paced, high performing team
  • Multicultural environment with over 60 different nationalities
  • Competitive Tax-free Salary
  • Comprehensive Health Insurance
  • Annual Air Ticket Allowance
  • Employee discounts at multiple vendors across the emirates
  • Rewards & Recognitions
  • Learning & Development

Dubizzle Group is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

#UAEdubizzle

Key Skills

Ranked by relevance

machine learning aws data visualization data warehousing matplotlib python pandas cloud sql ai
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Posted
Jan 07, 2025
Type
Full-time
Level
Mid-Senior
Location
Dubai
Company
dubizzle

Industries

Technology Information Internet

Categories

Engineering Information Technology

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