principal engineer

DNA INFOTECH PTE. LTD.; Singapore; On-site; SGD 200,000 - 260,000; Full time

Job summary

DNA INFOTECH PTE. LTD. seeks a Principal Scientist in Generative AI & NLP to lead R&D on LLMs, multimodal AI, and agentic systems. The role demands a strong publication record, deep algorithmic expertise, and hands-on experience building production-scale AI systems.

You will define research directions, push for high-impact papers, and drive scalable AI solutions that power next-generation products with on-premise deployment considerations.

Qualifications

• Ph.D. or master's in Computer Science, Machine Learning, Mathematics, Computational Linguistics, or a related field.
• 10–15 years of industry and/or academic experience in AI/ML, with 7+ years in NLP and Generative AI.
• Demonstrated leadership in publishing top-tier research in LLMs, multimodal models, or related areas.
• Proven experience in large-scale model training, optimization, and deployment.
• Expertise in Python, with proficiency in frameworks such as Hugging Face Transformers, TensorFlow, PyTorch, Keras, JAX.
• Deep understanding of LLMs, multimodal AI, embedding models, vector databases, and agentic AI.
• Experience with MLOps/LLMOps tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI).
• Strong system design skills, including distributed systems, data pipelines, and API development.

Responsibilities

• Define and drive the research roadmap in LLMs, multimodal AI, and Generative AI.
• Lead the authoring and publication of top-tier research papers (e.g., NeurIPS, ICML, ACL, CVPR).
• Stay at the forefront of AI advancements and translate research into practical, scalable solutions.
• Design and optimize novel algorithms for generative modeling, NLP, and agentic AI under system and compute constraints.
• Lead the development of high-performance training pipelines for large-scale models, including distributed training and inference optimization.
• Architect and implement end-to-end GenAI systems, including prompt orchestration, retrieval-augmented generation (RAG), and agentic workflows.
• Collaborate with engineering, product, and data science teams to integrate AI solutions into production environments.
• Build and maintain highly scalable backend microservices and real-time inference systems on cloud platforms (AWS, GCP, Azure).
• Mentor junior scientists / engineers in GenAI best practices and research methodologies.

Skills

Python programming

LLMs / Generative AI

NLP

Distributed training

Research leadership

Education

Ph.D. or Master’s in CS/ML/Math/ Computational Linguistics

Tools

Hugging Face Transformers

TensorFlow

PyTorch

Keras

JAX

MLflow

Weights & Biases

DVC

SageMaker

Vertex AI

Job description

We are seeking a Principal Scientist – Generative AI & NLP to lead our research and development efforts in cutting-edge AItechnologies, including Large Language Models (LLMs), multimodal AI, and agentic systems. This role is ideal for a seasonedAI researcher and technologist with a strong publication record, deep algorithmic expertise, and hands-on experience inbuilding and optimizing large-scale AI systems under real-world constraints. You will play a pivotal role in setting the researchdirection, leading high-impact publications, and driving the development of scalable, production-ready AI solutions thatpower next-generation products. The research direction is to achieve AI and Agentic system with emotional empathy, selflearning capability, multimodal memory for on-premise product deployment.

Key Responsibilities

• Research Leadership
  • Define and drive the research roadmap in LLMs, multimodal AI, and Generative AI.
  • Lead the authoring and publication of top-tier research papers (e.g., NeurIPS, ICML, ACL, CVPR).
  • Stay at the forefront of AI advancements and translate research into practical, scalable solutions.
• Algorithm & System Design
  • Design and optimize novel algorithms for generative modeling, NLP, and agentic AI under system and computeconstraints.
  • Lead the development of high-performance training pipelines for large-scale models, including distributedtraining and inference optimization.
• Product & Platform Development
  • Architect and implement end-to-end GenAI systems, including prompt orchestration, retrieval-augmentedgeneration (RAG), and agentic workflows.
  • Collaborate with engineering, product, and data science teams to integrate AI solutions into productionenvironments.
  • Build and maintain highly scalable backend microservices and real-time inference systems on cloudplatforms (AWS, GCP, Azure).
• Mentorship & Collaboration
  • Mentor junior scientists / engineers in GenAI best practices and research methodologies.
  • Work cross-functionally to align AI initiatives with business goals and customer needs

preferred qualifications

• Ph.D. or master’s in Computer Science, Machine Learning, Mathematics, Computational Linguistics, or a related field.
• 10–15 years of industry and/or academic experience in AI/ML, with 7+ years in NLP and Generative AI.
• Demonstrated leadership in publishing top-tier research in LLMs, multimodal models, or related areas.
• Proven experience in large-scale model training, optimization, and deployment.
• Expertise in Python, with proficiency in frameworks such as Hugging Face Transformers, TensorFlow, PyTorch, Keras, JAX.
• Deep understanding of LLMs, multimodal AI, embedding models, vector databases, and agentic AI.
• Experience with MLOps/LLMOps tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI).
• Strong system design skills, including distributed systems, data pipelines, and API development.