AI Innovator

19 hours ago

thiruvananthapuram, India beBeeGenerativity Full time

AI Research ScientistWe are seeking a skilled professional to join our fast-paced team as an AI Research Scientist. This role requires expertise in transformer architectures and strong fundamentals in model training, fine-tuning, and optimization.As an AI Research Scientist, you will work across multiple domains, with the flexibility to specialize in one area but also adapt to experiment with others. You will run rapid experiments, iterate on state-of-the-art models, and push the boundaries of generative AI in areas such as lip-sync, character consistency, audio realism, and video quality.Key Responsibilities:Model Development & Fine-tuning: Run end-to-end experiments on transformer-based architectures (LLMs, Whisper, diffusion, LoRA, RLHF/SFT, multimodal models).Domain-Specific Applications:Audio: Lip-sync, emotional delivery (shouting, whispering, crying), regional language support.Video: Scene/character consistency, quality benchmarks comparable to Veo3/Sora.Text: Extend LLMs to handle regional languages and domain-specific adaptation.Evaluation & Optimization: Design automated evaluation frameworks for objective quality scoring (images, video frames, audio clips). Balance trade-offs in speed, quality, and efficiency.Cross-Modality Integration: Experiment with audio-video synchronization, background score integration, and text-to-video alignment.Research & Experimentation: Stay ahead of rapidly evolving models and tools, testing architectural variations and scaling solutions for production use.Ownership & Execution: Drive initiatives independently with strong problem-solving, accountability, and first-principles thinking.Requirements:Experience: 4–10 years in applied Data Science/ML with a strong focus on generative AI.Core Fundamentals: Solid grasp of transformer architectures, LLMs, training dynamics, and optimization techniques.Modality Depth: Expertise in at least one modality (text, audio, or video), with demonstrable end-to-end project experience.Hands-On Skills: Strong coding and debugging ability in Python, with deep learning frameworks (PyTorch, TensorFlow).Deployment Knowledge: Experience with ML pipelines (FastAPI or similar) for inference and deployment.Evaluation Metrics: Proven ability to design/implement automated evaluation methods for generative outputs.Adaptability: Ability to experiment quickly with new tools, libraries, and models in a dynamic environment.Benefits:We offer a competitive salary and benefits package to attract the best talent in the industry.Our team is passionate about innovation and excellence, and we foster a culture that encourages growth and collaboration.

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