Pixalate is seeking a PhD-level AI Engineer to lead research in agentic AI systems, multimodal analysis, and advanced reasoning architectures.
The role is remote and based in Singapore, and it is a full-time position at a mid to senior level.
The AI Engineer will bridge the gap between fundamental AI research and production systems that enhance digital safety and fraud detection.
Responsibilities include designing multi-agent architectures for fraud detection, developing agent coordination systems, and creating tool-integrated AI agents.
The engineer will implement advanced reasoning systems and optimize inference-time compute allocation for analytical tasks.
The role also involves building multimodal models for analyzing various data types and researching cross-modal learning for fraud pattern detection.
Requirements:
A PhD in Computer Science, AI, Machine Learning, or a related field is required, or an exceptional research track record.
Candidates must have published research in peer-reviewed venues demonstrating expertise in large language models, agentic AI, multimodal learning, and distributed systems.
Expert proficiency in Python and deep learning frameworks, preferably PyTorch, is necessary.
Advanced experience with modern AI frameworks, agent development, RAG systems, and distributed training frameworks is required.
A strong understanding of transformer architectures, reinforcement learning, neural architecture search, and MLOps is essential.
A track record of novel algorithm development, experience with large-scale experimentation, and proficiency in research tools is expected.
Benefits:
The position offers a generous benefits package, including 25 days of holiday plus bank holidays.
Employees will have access to a defined contribution pension scheme and monthly internet reimbursement.
The work environment is casual and remote, with hybrid and flexible hours.
There are opportunities for advancement and participation in fun annual team events.
Employees will be part of a high-performing team with a focus on winning and having fun, along with extremely competitive compensation.