What You'll Do
Drive foundational research in generative AI, focusing on transforming experimental models into scalable, real-world applications. You'll lead technical innovation across key domains including multimodal processing, personalized AI experiences, and advanced knowledge retrieval systems.
Design and refine data pipelines to support large-scale training, while developing and optimizing training strategies across pre-training, mid-training, and post-training phases. Build and improve reinforcement learning frameworks that enhance decision-making and adaptive behaviors in AI systems.
Create intelligent architectures capable of understanding and generating content across text, audio, image, and video. Develop methods for representing and retrieving structured knowledge, enabling more accurate and context-aware AI responses.
Guide the evolution of AI models from early prototypes to production-grade solutions, ensuring robustness, scalability, and performance. Lead research initiatives that push the boundaries of what's possible in generative AI, publishing findings in top-tier venues and influencing the broader research community.
Collaborate with engineering and product teams to embed advanced AI capabilities into core products. Inform strategic technology planning by identifying emerging opportunities and assessing their alignment with long-term goals. Mentor researchers and engineers, fostering a culture rooted in curiosity, critical thinking, and continuous improvement.
Requirements
Hold a PhD or MSc in Computer Science, Machine Learning, or a closely related discipline. Bring at least eight years of experience in AI research, with a proven history of translating research into practical applications or products.
Demonstrate deep expertise in generative AI, with three or more years focused specifically on developing and refining large language models and related technologies. Possess hands-on experience building tools and infrastructure for data preprocessing, model training, fine-tuning, and deployment in both research and production settings.
Have strong foundations in distributed and parallel computing in cloud environments, along with fluency in Python and version control systems like Git. Show mastery across core areas including deep learning, probability theory, natural language processing, computer vision, and model evaluation.
Benefits
Work in an environment that values intellectual rigor, collaboration, and continuous learning. Engage in high-impact research with access to cutting-edge tools and infrastructure. Contribute to a culture that emphasizes problem-solving, empathy, adaptability, and humility, where challenging assumptions and learning from failure are encouraged.
Opportunities to publish and present work at leading conferences are supported, alongside mentorship and professional growth. The role is based in India, with a focus on building local research excellence within a globally aligned technical vision.
