ML Research Scientist

About Think

Think AI, founded in Riyadh in 2025, focuses on enhancing compute efficiency by integrating hardware and software design. The company aims to redefine AI infrastructure from the silicon up, building efficient compute platforms where hardware and software co-evolve to maximize intelligence. This approach seeks to enable scalable AI operations without compromise or wasted compute.

The Role: ML Research Scientist

Think is seeking an ML Research Scientist to join its team in Riyadh, Saudi Arabia. This full-time role involves conducting empirical research on the company's proprietary hardware to understand model behavior and inform platform development. The successful candidate will have over 10 years of experience in a relevant field.

Key Responsibilities

• Design and execute experiments on production fleets rather than synthetic proxies.
• Investigate model behavior under various conditions, including co-location, quantization, adapter serving, and mixed-precision execution.
• Translate research findings into actionable decisions for the orchestration layer and collaborate with engineering teams for implementation.
• Document and publish internal research with the same rigor expected for external publications, detailing methods, data, and limitations.
• Ensure accurate interpretation of research results within the team.
• Monitor relevant literature to distinguish validated findings from speculative claims.

Qualifications and Experience

• A minimum of 10 years of experience in a related field.
• Demonstrated ability to conduct empirical research and translate findings into practical applications.
• Experience working with hardware-software co-design or optimization is beneficial.

Working Environment and Benefits

This role offers the opportunity to contribute to one of the region's early deep tech companies, focusing on foundational technology development. The position provides significant ownership and impact within a small, senior team. Collaboration across hardware, systems, and AI at scale is a core aspect of the work. Compensation for this early-stage role is competitive.