Mathematical ML Algorithms Research Scientist

Remotedxb; Dubai; On-site; AED 260,000 - 420,000; Full time

Job summary

Remotedxb in Dubai is seeking a highly analytical researcher-developer to build numerical-analytical models of learning in our system and connect research to existing literature.

You will prove properties of algorithms, design experiments to validate results empirically, translate between equations and code, and write clean, well-documented software to help the team reach its goals. Collaboration with peers and rigorous experimentation are essential.

Qualifications

• Advanced degree or equivalent research experience in mathematics, CS, or statistics.
• Experience with mathematical analysis methods such as optimal transport, information geometry, or continuous optimization.
• Experience with probabilistic graphical models and factor graphs.
• Experience implementing tractable density estimators (normalising flows, autoregressive density models, probabilistic circuits).
• Ability to translate between equational reasoning and code implementation.

Responsibilities

• Develop numerical-analytical models of learning in our system.
• Connect our research to existing literature.
• Prove properties of algorithms and design experiments to validate results empirically.
• Leverage the expertise of other team members effectively.
• Write clean and well documented code.
• Help other team members to deliver on their goals.

Skills

Optimal transport

Information geometry

Continuous optimization

Probabilistic graphical models

Density estimators

Code implementation

Education

PhD or equivalent research experience

Job description

Remotedxb in Dubai is seeking a highly analytical researcher-developer to build numerical-analytical models of learning in our system and connect research to existing literature.

You will prove properties of algorithms, design experiments to validate results empirically, translate between equations and code, and write clean, well-documented software to help the team reach its goals. Collaboration with peers and rigorous experimentation are essential.