Lead AI Engineer

About Impact Analytics

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 to forecast and plan this year's business. Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery,

manufacturing, and CPG sectors. In 2025, Impact Analytics is at the forefront of the Agentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention.

Here's a link to our website: www.impactanalytics.co.

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.

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
• at least 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 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.

Some of our accolades include:

● Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.

● Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.

● Voted #1 by more than 300 retailers worldwide in the RIS Software Leader Board 2024 report.

● Ranked #72 in America's Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.

● Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.

● Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.