Data Scientist Specialist

1 week ago

Koṭa, India beBeeDataScience Full time

Job Title: Data ScientistWe're seeking an expert data scientist with a strong background in applied AI/ML to drive our team's success.Model Development & Fine-tuning: Experiment with transformer-based architectures (LLMs, Whisper, diffusion, LoRA, RLHF/SFT, multimodal models) to enhance our solutions.Domain-Specific Applications:Audible features such as lip-sync, emotional delivery (shouting, whispering, crying), regional language support for improved user experience.Video: Ensure scene/character consistency and quality benchmarks comparable to Veo3/Sora.Text: Extend LLMs to handle regional languages and domain-specific adaptation for more effective communication.Key Responsibilities:Evaluation & Optimization: Design automated evaluation frameworks for objective quality scoring (images, video frames, audio clips). Balance trade-offs in speed, quality, and efficiency to achieve optimal results.Cross-Modality Integration: Experiment with audio-video synchronization, background score integration, and text-to-video alignment to create seamless experiences.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 to deliver successful outcomes.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.

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