Chief Generative AI Architect

3 days ago

erode, India beBeeArtificialintelligence Full time

AI/ML Data SpecialistWe're seeking a highly skilled AI/ML professional with 4–10 years of experience in applied machine learning to join our fast-paced research team.This role demands deep expertise in transformer architectures and strong fundamentals in model training, fine-tuning, and optimization.You will work across text, audio, and video modalities, with the opportunity to specialize deeply in one area while maintaining versatility to experiment across others.Key Responsibilities:Run end-to-end experiments on transformer-based architectures (LLMs, Whisper, diffusion, LoRA, RLHF/SFT, multimodal models).Prototype, benchmark, and push the limits of emerging generative AI techniques.Domain-Specific Applications:Auditory domain:Lip-sync accuracyEmotional delivery (whispering, shouting, crying)Regional language model supportVisual domain:Character & scene consistencyQuality outputs comparable to Veo3/SoraMotion smoothness & frame coherenceTextual domain:Extend LLMs to handle regional languagesBuild domain-adapted, fine-tuned modelsEvaluation & Optimization:Build automated evaluation pipelines for audio, video, and image quality scoring.Optimize trade-offs between speed, quality, and compute efficiency.Cross-Modality Integration:Experiment with audio–video synchronization.Integrate background score generation and text-to-video alignment.Push the boundaries of multimodal generative systems.Research & Experimentation:Stay ahead of rapidly evolving AI models, tools, and techniques.Test architectural variations and scaling strategies for production-ready systems.Required Skills:4–10 years in applied ML/Data Science with significant generative AI experience.Core Fundamentals:Deep understanding of transformer architectures, training dynamics, and model optimization.Experience with LLMs, diffusion models, and multimodal architectures.Modality Expertise:Depth in at least one modality (text, audio, or video) with end-to-end project delivery.Technical Skills:Strong coding skills in Python.Expertise with frameworks like PyTorch or TensorFlow.Experience with deployment frameworks (e.g., FastAPI, model servers).Evaluation Experience:Ability to design and implement automated evaluation systems for generative outputs.Adaptability:Comfort with rapid experimentation and learning new tools, models, and techniques.

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