Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end‑to‑end platform for planning, forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real‑time insights rather than relying on last year’s inputs.
The Impact That You Will Be Making
- 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 (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 Lands You In This Role
- At least 5–9 years in Software & Machine Learning, with at least 2–3 years in Generative AI and 5–6 years in:
- Deep Learning
- Computer Vision or Natural Language Processing
- Strong conceptual knowledge of:
- Generative modeling techniques (e.g., Autoencoders, Diffusion & Transformer architectures)
- Efficient fine‑tuning mechanisms (e.g., Adapter training, Multi‑task learning, etc.)
- Hyperparameter optimization (especially Bayesian & Multi‑fidelity 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.
- Preferred: Experience building or fine‑tuning LLMs.
- Preferred: Masters or Ph.D. in computing/systems, mathematics, machine learning or related areas.