Posted on: 25/05/2026
Description :
Impact Analytics builds AI-powered, cloud-native products and platforms. As we tackle increasingly complex backend challenges, we are looking for seasoned backend architects to collaborate with product and engineering teams in shaping the future of enterprise software.
Responsibilities :
- Build cutting-edge GenAI solutions, leveraging both external assets (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 the CTO to design and 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.
Requirements :
- Computer Vision or Natural Language Processing.
- Strong conceptual knowledge of generative modelling techniques (e. g., Autoencoders, Diffusion and Transformer architectures); Efficient Fine-tuning mechanisms (e. g., Adapter training, Multi-task learning, etc. ); and hyperparameter optimisation (especially Bayesian and Multi-fidelity Optimisation 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 a Master's or PhD in computing/systems, mathematics, machine learning or related areas will be preferred.
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