Research Scientist

Title:

AI Research Scientist We are seeking a highly skilled and innovative ResearchScientist specializing in Artificial Intelligence to join our R&&D team. This role is idealfor someone with deep expertise in implementing and customizing state-of-the-art AIresearch papers, optimizing large-scale models, and building robust datasets. Youwill work on real-world applications of generative AI, large language models (LLMs),and computer vision systems, contributing directly to the development of scalableand impactful AI solutions. Key Responsibilities Implement and customize cutting-edge AI research papers into working prototypes and production-ready models. Conduct performance improvement experiments on large-scale models, includingfine-tuning, prompt engineering, and architecture modifications. Develop and manage training and evaluation datasets, including synthetic datageneration, annotation pipelines, and benchmark creation. Collaborate with engineering and product teams to deploy research outputs intoscalable systems. Stay up-to-date with the latest advancements in AI and contribute to internal researchstrategy. Document experiments, share insights, and support innovation through patent filingsand technical reports.Required Qualifications

Ph.D. or Masters degree in Computer Science, Artificial Intelligence, MachineLearning, or a related field. Proven experience in implementing and customizing AI research papers (e.g., fromarXiv, NeurIPS, ICML). Hands-on experience with Large Language Models (LLMs): GPT, LLaMA, Mistral,Falcon. Experience with Vision Models: ViT, SAM, CLIP. Experience with Generative Models: Stable Diffusion, DALLE, GANs. Experience with Multimodal Systems combining vision, language, and audio. Proficiency in Python, PyTorch, TensorFlow, JAX. Experience with Hugging Face Transformers, Diffusers, OpenAI Gym. Experience with Weights && Biases, MLflow, TensorBoard. Internal - General Use AIExperience with Distributed training: DeepSpeed, FSDP, Horovod. knowledge of Model optimization: quantization, pruning, distillation. Experience with Data tools: DVC, Apache Arrow, Label Studio. Strong understanding of evaluation metrics, benchmarking, and reproducibility.