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.

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.

Best in class salary: We hire only the best, and we pay accordingly.
Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.

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