Senior Technologist - Machine Learning

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

• Design and own CNN, U-Net, and ViT systems for precision inspection, measurement, and defect classification.
• Build real-time anomaly detection systems using sensor and time-series product development data.
• Validate and deploy physics-informed neural networks and surrogate model pipelines for product development.
• Architect active learning and Bayesian experimental design pipelines integrated with laboratory scheduling and instrument control systems.
• Own the ML platform across MLflow, Docker, AWS EKS/Kubernetes, LLM gateways, CI/CD, observability, and model monitoring.
• Lead design and code reviews, define data interface contracts, collaborate with domain scientists, and mentor junior engineers.

Requirements

• Bachelor’s or Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
• 3–5 years of hands-on technical experience owning AI systems from design through product development deployment.
• Experience directing a small ML or AI engineering team, including design reviews, mentoring, and cross-functional delivery.
• Expert-level Python and PyTorch proficiency, including custom loss functions and full training loop ownership.
• Experience with computer vision, anomaly detection, surrogate modeling, active learning, Bayesian experimental design, and product development MLOps.
• Experience with MLflow, Docker, AWS EKS, and observability or LLM gateway platforms such as LangFuse or PortKey.

Nice to have

• Experience in materials science, semiconductors, precision product development, or scientific and industrial AI.
• Experience validating physics-informed neural network designs and building physics-constrained models.
• Experience with reinforcement learning, RAG or GraphRAG, RLHF, reward modeling, LLM fine-tuning, or distillation.
• Significant open-source ML contributions, public technical writing, or a documented GitHub portfolio.

Culture & Benefits

• Work on AI infrastructure and storage systems supporting hyperscale data centers, cloud platforms, and enterprise infrastructure.
• Collaborate across engineering, data, and scientific disciplines on systems deployed at production scale.
• Inclusive workplace focused on diversity, belonging, respect, and contribution.
• Accessibility support is available throughout the application and hiring process.