| Company | Agio |
| Job title | AI Engineer |
| Job location | Remote |
| Type | Full time |
| Job post date | 18th April 2024 |
Calling all data detectives with a passion for AI! We’re looking for an AI Engineer to join our team and unlock the hidden potential within our vast IT service data. Your expertise in machine learning will be key in building powerful models that integrate seamlessly with our data warehouse, monitoring platforms, and delivery systems. These models will be the driving force behind innovative, data-driven products that revolutionize how we handle IT services.
Get ready to dive deep into the world of Natural Language Processing (NLP). You’ll be wielding cutting-edge Large Language Models (LLMs) to develop next-level solutions. Imagine – NLP that can not only categorize and route IT issues with laser focus, but also provide insightful context and troubleshooting suggestions. Your models will empower our teams to resolve issues faster and more effectively than ever before.
Ultimately, your work will be instrumental in making data-driven decisions that lead to the creation of intelligent, model-driven products. If you’re an AI Engineer who thrives on tackling complex challenges and has a knack for extracting valuable insights from data, then we want you on our team! Join us and be the data hero we’ve been searching for.
Responsibilities:
- Create NLP solutions: Utilize your expertise in NLP and hands-on experience with language models like BERT, GPT, etc. to develop and deploy cutting-edge NLP solutions for various applications
- Model Development: Manage model development and prototype lifecycle from data sourcing to model training and/or prompt engineering to deployment
- Team Collaboration: Work closely with the rest of the product team, data science, and engineering to build concepts and requirements
- Data Analysis: In depth data analysis and visualization to provide insight into company efficiency and performance. Work with data engineering to process, cleanse, and verify the integrity of the data used for analysis
- Assist in project delivery: Take ownership of ML projects, manage timelines, and ensure successful project delivery. Collaborate with cross-functional teams, including data engineers, software engineers, and product managers, to define project requirements and deliverables
- Research and stay up to date: Stay abreast of the latest advancements in NLP, machine learning, and deep learning technologies. Conduct research to explore new methodologies, tools, and algorithms that can enhance our existing systems
