Applied Deep Learning Researcher - Quantitative Alpha

Millennium; Dubai; On-site; AED 450,000 - 850,000; Full time

Job summary

Millennium in Dubai is seeking a senior research-focused ML engineer to design and deploy core deep learning pipelines for quantitative research—from data prep and distributed training to production deployment.

The ideal candidate has top-tier academia with a PhD-level background, hands-on experience with large models, solid ML theory, and a track record in rigorous evaluation and reproducible research practices.

Qualifications

• Top-tier academic background with PhD-level training in a quantitative field.

Responsibilities

• Design and build core deep learning pipelines for applied quantitative alpha research—from data preparation to production deployment.
• Drive the research agenda using applied deep learning, owning the full empirical loop: problem formulation, model design, training, validation, and attribution.
• Uphold rigorous research discipline with out‑of‑sample hygiene, leakage prevention, and fair benchmarking against baselines.
• Advise on architecture selection and training diagnostics, review model designs, set standards for evaluation and promotion.
• Facilitate seamless model fitting and computation across teams via standardized training and inference interfaces.

Skills

Deep learning

Python

Distributed training

Model evaluation

Statistics & ML theory

Experiment tracking

Communication

Education

PhD level training in CS/Engineering/Physics/Math/Stats

Graduate from top-20 university

Tools

CUDA

PyTorch/TensorFlow

LLM tooling

Distributed training frameworks

Job description

Millennium in Dubai is seeking a senior research-focused ML engineer to design and deploy core deep learning pipelines for quantitative research—from data prep and distributed training to production deployment.

The ideal candidate has top-tier academia with a PhD-level background, hands-on experience with large models, solid ML theory, and a track record in rigorous evaluation and reproducible research practices.