Are you looking for a challenging yet rewarding project that will leverage the best of your decision-making and engineering excellence?

At DIAL we strive to maintain a delicate balance between the constantly evolving LLM landscape, the demands and scales of enterprise customers, and the restrictions that come with developing an open-source multimodal LLM and Application Orchestration platform under the Apache 2 license, all while ensuring ease of use and deployment and constantly delivering new features.

Using DIAL as a foundation, we build a variety of practical solutions that can be customized for specific needs, such as StatGPT, a talk-to-your-data platform adopted by the International Monetary Fund and World-Bank. Imagine a future where accessing and understanding complex datasets is as easy as asking a question. With Project StatGPT, that future is now. We're on a mission to democratize data access through the power of Large Language Models (LLMs) based on Natural Language Processing (NLP). StatGPT is designed to bridge the gap between vast data repositories and the business people who need insights from them, using intuitive, conversational interfaces.

To excel in this position, there are specific abilities and skills that are essential. Yet, we understand that not everyone may possess every desired skill initially. If you are confident in your capacity to learn and adapt, we welcome you to develop any missing skills through hands-on experience once you're on board. Tell us what your strong side is and we will find the right task for you

Responsibilities

Design and develop AI/ML-enabled solutions to search, visualize and explain data from various sources (data warehouses, databases)
Compare performance of different LLMs for particular business problems
Test and evaluate AI/ML solution with objective to meet defined criteria for accuracy and coherence
Contribute to continuous improvement of solution performance and cost efficiency

Requirements

University degree in Computer Science, Data Science or equivalent practical experience
Deep understanding of capabilities and challenges of applying Generative AI in business context
Familiarity with GenAI/LLM frameworks (e.g. Langchain, LlamaIndex, haystack)
Proficiency in Python and hands-on experience with ML frameworks and platforms (e.g. Tensorflow, PyTorch, MLflow)
Experience working with multi-dimensional data cubes and building analytics on top of them
Ability to work in cross-functional teams in a dynamic business environment based on agile development principles
Capability to describe business use-cases, implementation vision and technology choices for both technical and non-technical audiences