AI Research Scientist, Scientific ML

Location: Singapore office

Company

hirify.global develops storage systems and infrastructure for AI-driven data centers, cloud platforms, and enterprise environments.

What you will do

• Originate and advance scientific machine learning methodology based on physics-informed neural networks (PINNs).
• Design physics-constrained loss functions and validate digital twin machine learning components against domain physics.
• Lead research in Bayesian deep learning, active learning acquisition functions, uncertainty quantification, and Bayesian experimental design, or develop causal machine learning frameworks for reliability root cause analysis.
• Design physics-constrained generative models, including diffusion models and VAEs, for synthetic data generation.
• Deliver validated research prototypes, training recipes, and complete technical documentation for engineering implementation.
• Collaborate with storage domain experts and participate in design reviews as the research methodology authority.

Requirements

• Master’s or PhD in artificial intelligence, machine learning, physics, applied mathematics, or a related field, with a strong scientific computing background.
• Expert research-level implementation skills in PyTorch or JAX.
• Demonstrated experience designing PINNs methodology, physics-constrained loss functions, and digital twin models.
• Experience in either Bayesian and uncertainty quantification methods or causal machine learning for reliability and yield root cause analysis.
• Research output such as a publication, preprint, PhD thesis chapter, or significant open-source scientific ML contribution.
• Ability to produce validated research prototypes with complete technical documentation for handoff.

Nice to have

• Diffusion models, graph neural networks, Neural ODEs, foundation model fine-tuning, or reinforcement learning for scientific discovery.
• Top-venue publications in NeurIPS, ICML, ICLR, Nature Machine Intelligence, or related venues.
• Background in materials science, semiconductors, or precision product development.

Culture & Benefits

• Work on storage systems supporting hyperscale data centers, cloud platforms, and enterprise infrastructure.
• Research is validated against physical ground truth and applied to real product development problems.
• Inclusive environment focused on diversity, belonging, respect, and contribution.
• Candidate accommodations are available throughout the application and hiring process.