Principal AI Research Engineer — Energy
Remote - Saudi
Principal / Frontier-Level Individual Contributo- r60% research · 40% production engineerin
g
ABOUT CLIE
NT
A Saudi technology and engineering company developing advanced systems across artificial intelligence, energy, critical infrastructure, security, and industrial technolo
gy.
European expansion will establish a multidisciplinary AI laboratory bringing together advanced AI researchers, mathematicians, energy specialists, AI engineers, and software develop
ers.
THE
ROLE
Seeking an exceptional Principal AI Research Engineer — Energy Systems to help establi
sh andlead the technical direction of its frontier AI research programme. This is not a conventional machine-learning engineering position. The successful candidate will operate between advanced research, scientific computing, energy-system intelligence, and large-scale AI engine
ering.
You will investigate new AI methodologies, build experimental systems, validate them against real-world energy data, and lead the transition of successful research into secure, production-grade solutions deployed on private GPU infrastr
ucture.
You will also serve as a technical leader for growing AI team, mentoring AI researchers and engineers, setting scientific and engineering standards, and helping define the company's long-term AI research
roadmap.
KEY RESPONS
IBILITIES
▪ Define and lead ambitious research programmes at the intersection of artificial intelligence, applied mathematics, scientific computing, and energ
y systems.▪ Develop novel architectures, algorithms, training strategies, and evaluation methodologies for complex energy and industrial
problems.▪ Research advanced approaches including physics-informed neural networks, graph neural networks, neural operators, probabilistic modelling, representation learning, reinforcement learning, control-aware learning, and foundation models for time-series and se
nsor data.▪ Design scientifically rigorous experiments, benchmarks, ablation studies, and validation
protocols.▪ Translate successful research into reliable prototypes and production-grade A
I systems.▪ Lead and mentor AI research engineers, machine-learning engineers, and supporting AI
engineers.▪ Help shape long-term AI research strategy, compute strategy, and technica
l roadmap.
TECHNICAL
ENVIRONMENTThe exact stack will evolve, and the successful candidate will have significant influence over its
direction.
▪ Python · PyTor
ch 2.x · JAX▪ NumPy, SciPy, Pandas and Polars · scikit-learn · XGBoost
and LightGBM▪ PyTorch Geometric or equivalent graph-learnin
g frameworks▪ Probabilistic programming and Bayesian mod
elling tools▪ Optimization frameworks such as Pyomo, CVXPY, OR-Tools o
r equivalent▪ MLflow for experiment tracking, model lineage and registr
y management▪ Kubeflow Trainer and Kubefl
ow Pipelines▪ Git and modern code-review workflows · CI/CD for AI and scientific-computi
ng workloads▪ Data and model versioning · automated evaluation and regres
sion testing
Candidates are not expected to have used every listed technology. They must, however, demonstrate deep expertise in the underlying principles and the ability to rapidly evaluate and adopt appro
priate tools.
REQUIRED
QUALIFICATIONS▪ Exceptional expertise in machine learning, deep learning, applied mathematics, scientific computing, statistics, control, optimization, or a closely relat
ed discipline.▪ A demonstrated record of solving technically difficult AI or computati
onal problems.▪ Deep proficiency in Python and at least one major deep-learning framework, preferably P
yTorch or JAX.▪ Strong mathematica
l foundations.▪ Experience designing, training, evaluating, and debugging advanced machine-le
arning models.▪ Experience taking research from an initial hypothesis through experimentation, validation, implementation, and operation
al deployment.▪ Evidence of technical leadership through mentoring, architecture ownership, research leadership, opensource contributions, publications, patents, or delivery of maj
or AI systems.▪ Ability to communicate complex scientific and engineering con
cepts clearly.▪ Professional fluen
cy in English.