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NCS

ICT consulting, digital transformation, cybersecurity services

Senior LLM / Multimodal AI Engineer

Computer Vision +1Confirmed live in the last 24 hours
Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

  • At least 4 years of hands-on experience in machine learning system development, with demonstrated focus on natural language processing, computer vision, large language models, or multimodal artificial intelligence.
  • A proven track record of independently driving end-to-end machine learning initiatives from research exploration to high-throughput production deployment.
  • Deep expertise in deep learning fundamentals, transformer architectures, and multimodal fusion techniques.
  • Proficiency in PyTorch, the Hugging Face ecosystem, DeepSpeed, PEFT, and LlamaFactory.
  • Strong programming capabilities in Python, SQL, Spark, and Linux/Git workflows.
  • Hands-on experience with vector search and retrieval infrastructure, including FAISS and multimodal retrieval-augmented generation.
  • Familiarity with large language model and vision-language model serving and quantization toolkits, including vLLM, TensorRT-LLM, and Triton.

Responsibilities

  • Architect and scale automated data pipelines integrating video frames, images, optical character recognition, automatic speech recognition, and text for vision-language model pre-training and fine-tuning.
  • Drive large language model-assisted annotation workflows and synthetic data generation strategies to minimize manual labeling overhead.
  • Engineer data quality frameworks to ensure representative, accurate, and complete training datasets.
  • Reproduce and optimize foundation model series, such as LLaVA and the Qwen-VL family, for production environments.
  • Execute supervised fine-tuning and post-training for domain-specific content ecosystems, including gaming, movies, automotive, and commercial advertising.
  • Implement advanced training techniques, including parameter-efficient fine-tuning, low-rank adaptation, and quantization-aware training.
  • Design and deploy hierarchical retrieval-augmented generation pipelines that enrich video understanding and enable in-context retrieval.
  • Build scalable vector search indexes, such as FAISS, supporting billions of embeddings.
  • Optimize retrieval strategies, including hybrid search, re-ranking, and query expansion.
  • Optimize large-scale vision-language model and large language model serving using vLLM, TensorRT-LLM, Triton, and ONNX Runtime.
  • Implement dynamic batching, feature caching, and asynchronous scheduling to maximize GPU throughput.
  • Monitor and tune production inference systems for latency, cost, and quality trade-offs.
  • Establish comprehensive online and offline evaluation benchmarks measuring generative quality, aesthetic completeness, and vertical task precision and recall.
  • Contribute to intelligent tag platform agents and agentic workflow orchestration.
  • Conduct continuous large language model-as-judge evaluation on production traces.

Desired Qualifications

  • Industrial experience in large-scale recommender systems, advertising technology, or content moderation and understanding ecosystems.
  • Hands-on expertise with reinforcement learning from human feedback or preference optimization, such as DPO or GRPO.
  • Published research or competitive achievements in top artificial intelligence and machine learning venues or challenges, such as CVPR, NeurIPS, ICLR, or Kaggle.
  • Experience with cloud machine learning platforms, including AWS SageMaker, Azure ML, or Google Vertex AI.
  • Knowledge of artificial intelligence observability tools, including Langfuse, Weights & Biases, or MLflow.

About the Company

NCS

ICT consulting, digital transformation, cybersecurity services

NCS delivers ICT services in the Asia Pacific region, including consulting, digital transformation, technology solutions, and cybersecurity for government and private sector clients. It offers advisory, implementation, and managed services, supported by three innovation centers in Singapore, Melbourne, and Shenzhen and a workforce of about 13,000 across 20 cities. The company emphasizes long-term client partnerships, regional scale, and practical solutions developed at its innovation centers. Its goal is to help clients navigate digital transformation and cybersecurity while maintaining ethical conduct and transparent governance.

Company size
10,001+
Company stage
Grant
Total funding
$780K
Headquarters
Singapore, Singapore
Founded
1981

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