What you'll do :

• Solve complex business problems of the global supply chain & retail industry through Machine Learning, especially leveraging Generative AI.
• Build cutting-edge GenAI solutions, leveraging both external assets (e.g., OpenAI/GCP Models) and IA’s proprietary models, to address real-world problems efficiently.
• Play a critical role in developing/evolving IA’s industry-disrupting Foundational Model for Forecasting, and integrating the same into various product offerings.
• Deliver AI R&D objectives for one or more projects, and work with other AI architects and CTO to design & develop new Deep Learning/GenAI architectures and algorithms.
• Contribute to the IP generation process in the company, and work towards patenting key inventions.
• Collaborate with various stakeholder groups to identify opportunities for applying GenAI to solve real-world problems.

What makes you a great fit :

• At least 8-10 years in Software & Machine Learning with: (a) at least 2-3 years in Generative AI, and (b) at least 5-6 years in: Deep Learning, Computer Vision or Natural Language Processing
• Strong conceptual knowledge of: (a) Generative modeling techniques (e.g., Autoencoders, Diffusion & Transformer architectures), (b) Efficient Fine-tuning mechanisms (e.g., Adapter training, Multi-task learning, etc.) and (c) Hyperparameter Optimization (especially Bayesian & Multi-fidelity Optimization techniques.)
• Strong understanding of the global GenAI ecosystem, and how it continues to evolve.
• Proficiency in Python, and associated frameworks like TensorFlow or PyTorch.
• Strong communication skills, including the ability to explain advanced technical concepts, ideas, and solutions to both technical and non-technical collaborators.
• Ability to work under minimal supervision and in a fast-paced environment..
• Candidates with prior experience in building or fine-tuning LLMs will be given preference.
• Candidates with Masters or Ph.D. in computing/systems, mathematics, machine learning or related areas will be preferred.