01Key Responsibilities
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Implement and customise state-of-the-art AI research papers into working prototypes and production-ready models.
Conduct experiments to improve model performance through fine-tuning, prompt engineering, architecture optimisation, and evaluation.
Develop and manage training and evaluation datasets, including synthetic data generation, annotation workflows, and benchmark creation.
Collaborate with engineering and product teams to integrate AI research into scalable production systems.
Stay current with advancements in AI research and contribute to research planning and technical innovation.
Document experiments, technical findings, and contribute to patents, technical reports, and reusable research assets.
Ensure reproducibility, benchmarking, and responsible AI practices across research activities.
Required Skills:-
Robust expertise in Large Language Models (LLMs), Generative AI, multimodal AI, and computer vision.
Experience implementing AI research papers from leading research conferences and publications.
Proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience with Hugging Face Transformers, Diffusers, MLflow, TensorBoard, or similar machine learning tools.
Knowledge of distributed training frameworks such as DeepSpeed, FSDP, or Horovod.
Experience with model optimisation techniques including quantisation, pruning, and knowledge distillation.
Familiarity with data management and annotation tools such as .
