AI Scientist, Staff (Scientific Systems)

Location: one-north, Singapore

Employment Type: Full-Time, Permanent (on-site)

Department: R&D

About the Company

Galatek stands at the forefront of scientific and technological innovation, serving as a catalyst for global transformation. Headquartered in Singapore, with R&D and delivery centres in Germany, the United States, and China, our global presence reflects our commitment to delivering top-tier solutions and being a responsible global citizen. With an unwavering commitment to enhancing human life and shaping a more vibrant, resilient, and sustainable future, we empower the world's brightest minds to push the boundaries of possibility.

Galatek is an ambitious start-up fuelled by a diverse team of exceptional talents from leading global universities. United by a shared vision of innovation, we are pioneering advancements in robotics automation and artificial intelligence, transforming their applications in Biopharmaceutical and Semiconductor Manufacturing. By providing cutting-edge production tools, we liberate researchers and innovators from routine tasks, enabling them to focus on discovery and advancement. From life sciences and clinical diagnostics to applied chemicals, integrated circuits, and sustainable energy, we ignite a wave of breakthroughs that redefine industries and drive meaningful progress.

About the Role

At Galatek Singapore, we are building the next generation of advanced semiconductor equipment. We are seeking a high-caliber Lead AI Systems Architect (Closed-Loop Discovery) to own the 0 → 1 design and deployment of an AI platform that translates abstract scientific intent into execution-ready experimental realities.

In this foundational role, you will architect systems built specifically for high-complexity, real-world laboratory environments - where scientific intent is fluid, experimental data is multi-modal and noisy, and operational conditions are partially observable. You will bridge natural language reasoning, multi-modal machine learning, and dynamic planning engines to power Galatek’s next-generation scientific automation platform.

Key Responsibilities

1. AI System Architecture & Foundation (0 → 1)

• Architect and deploy modular, production-grade AI system architectures integrating natural language understanding (NLU), reasoning engines, and automated data ingestion layers.
• Ensure system reliability, determinism, and robust operation under unsimulated, real-world laboratory constraints.

2. Scientific Intent Translation

• Build intelligent translation models capable of interpreting loosely defined, ambiguous, or evolving scientific goals.
• Convert high-level scientific hypotheses into structured, testable, and machine-executable experimental objectives.

3. Dynamic Experiment Planning & Decomposition

• Develop decision and planning engines (LLM agents, adaptive planners) that decompose complex scientific workflows into actionable step-by-step execution plans.
• Optimize experiment execution sequences against real-time operational constraints (time, resource availability, cost, and physical hardware limitations).
• Enable dynamic, real-time plan adaptation based on intermediate experimental feedback and unexpected outputs.

4. Multi-Modal Experiment-to-Insight Engine

• Build multi-modal data interpretation layers to process and analyze diverse scientific outputs (including vision/imagery, numerical datasets, and time-series sensor streams).
• Extract structured knowledge and underlying physical trends from noisy, incomplete experimental inputs.
• Quantify and communicate mathematical uncertainty and confidence metrics across all model predictions and experimental results.

5. Closed-Loop Feedback & Active Learning

• Design and implement continuous feedback loops that synthesize historical experimental outcomes to continuously refine future test designs.
• Drive active learning mechanisms to maximize discovery rates, optimize resource efficiency, and accelerate scientific iteration cycles.

Key Requirements

Core Experience

• 8+ years of hands-on experience in applied AI / Machine Learning, with a track record of architecting and deploying complex AI platforms in production environments.
• Demonstrated experience building feedback-driven, closed-loop, or active learning systems operating on physical or real-world data streams.

Technical Expertise

• Planning & Reasoning Systems: Deep proficiency in LLM agents, decision engines, automated planning, or cognitive architectures.
• Multi-Modal ML: Hands-on experience modeling multi-modal datasets (combining text, vision, time-series, and tabular data).
• Uncertainty & Adaptive Modeling: Expertise in probabilistic modeling, uncertainty quantification, time-series modeling, or reinforcement learning (RL) / adaptive control.

Preferred Qualifications (Nice-to-Have)

• Prior exposure to Life Sciences, Biopharma, Synthetic Biology, or Applied Chemistry domains.
• Experience working within scientific computing, laboratory automation, or deep-tech research environments.
• Background in early-stage, high-growth, or deep-tech AI startups.

Why Join Galatek?

• Deep-Tech Impact: Work on zero-to-one precision engineering challenges that directly power the global semiconductor supply chain.
• Global Talent Culture: Collaborate with multidisciplinary R&D experts across Singapore and international hubs.
• Fair & Inclusive Workplace: Galatek adheres strictly to the Singapore Employment Act and Tripartite Guidelines on Fair Employment Practices (TAFEP). We evaluate all candidates based on merit and skill, and assist qualified global talent with MOM work pass applications.