Multimodal GenAI Architect / AI-ML Engineer

Were looking for an engineer who can adapt and extend GenAI architectures - training and testing modifications tailored to specific use cases and applications.

Key Responsibilities:

Develop Multimodal Architectures: Design, train, and test AI models capable of processing, understanding, and fusing inputs from multiple modalities (text, image, audio, video, etc.).

Data Pipeline Design: Build scalable pipelines for data collection, temporal alignment, and normalization across modalities.

Model Optimization: Improve performance, latency, and contextual accuracy of multimodal models in production environments.

Architecture Modification: Adapt and fine-tune existing GenAI/foundation model architectures to meet specific application requirements.

Required Skills:

Strong foundation in deep learning, LLM integration, and AI/ML programming frameworks (PyTorch).





Hands-on experience fine-tuning foundation models.

Experience with multimodal model architectures (e.g., vision-language models, audio-text fusion).

Solid understanding of model evaluation, testing, and production deployment practices.

Nice to Have:

Experience with distributed training / large-scale model training.

Familiarity with MLOps tools for pipeline automation and model monitoring.

Experience: 3-5 years Employment Type: Full time Availability: Immediate joiners"

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📌 GenAI / AI-ML Experts (Bengaluru)
🏢 KPIT
📍 Bengaluru