Apply on
Availability Status
This job is expected to be in high demand and may close soon. We’ll remove this job ad once it's closed.
Description:
The objective of the project is to solve industry problems in aviation, security and defense using language-model-powered Retrieval-Augmented Generation (RAG) & Agentic AI*. The end goals include proof-of-concept (POC) demonstrators to business partners. The challenges are to tailor the system to the unique business requirements, as well as to keep up with the breakneck pace of breakthroughs in LLM. The work involves entire machine-learning lifecycle including data exploration, data preparation (cleaning/transforming/annotation), and model serving/testing/tuning.
Responsibilities:
Right-size the computing hardware / software for the jobs
Collect / clean / transform / annotate data
Survey / select / develop / compare candidate LLM models and serving frameworks
Develop software codes to automate entire machine-learning lifecycle
Requirements:
Hands-on experience with machine learning
Proficient in at least two programming languages e.g. shell, Python, R, Matlab, C
Preferably experience with Generative AI, especially using API calls with chat completion, vector embedding and function calling
Preferably experience in making, serving and proxying API calls e.g. HTTP
Keen interests in machine-learning operations for scale up and fast iteration
Team player
Expected Outcome:
Demonstration of a working system with well-defined end-to-end test scenarios
Documentation of the finding, design and test cases / results
Team sharing and communication of various forms, including but not limited to live demo, video and workshops
- https://www.forbes.com/sites/bernardmarr/2024/09/06/agentic-ai-the-next-big-breakthrough-thats-transforming-business-and-technology/