Medical information is difficult. It’s true for both the general public and medical professionals.
Today, countless cancer patients are struggling to understand the incomprehensible test results they receive from hospitals. Many medical professionals who cannot provide many explanations in a short time also feel sorry.
Tesser creates AI technologies and services that allow patients and doctors to understand and utilize medical information more easily. From severe diseases like cancer to health check-ups, we are creating a new culture where anyone can utilize AI and data to understand and manage their health.
[Products Developed at Tesser]
＜Ontol (Mobile App)＞
A patient app that allows users to easily understand test results just by taking a photo, and offers various services to manage health starting from chatbot and community.
＜Hospital SaaS＞
An AI SaaS (in development) that provides more understandable, customized explanations of test results at hospitals and health examination centers.
[What We Do at Tesser]
Ontol is an early-stage service that is rapidly growing as it is shared among patients.
Tesser continuously identifies problems to 1) more effectively address the difficulties patients face and 2) ensure that anyone can use it easily and conveniently through AI technology and services.
▶ Tesser Introduction and Recruitment Page
https://career.tesser.co.kr
▶ Tesser Homepage
https://www.tesser.co.kr
• Develop and research algorithms for optimization of an LLM (Large Language Model) that performs various tasks using medical data.
• Implement model optimization and distribution environment optimization, establish AI Ops and a reliable inference environment.
• Develop prompt chains suitable for tasks and RAG, and multimodal APIs.
[We are looking for candidates with research experience in the following areas]
• Processing natural language models based on Transformer such as BERT, Hugging Face
• Inference optimization using open-source model optimization and engines (ONNX, TensorRT, etc.)
• Implementing models using Pytorch-based training frameworks (DeepSpeed, Accelerate, Bitsandbyte, etc.)
• Analyzing requirements necessary for commercializing LLM-based services and implementing them directly
• Actual implementation related to LLM-based service evaluation and system development
[We hope to work with individuals who have]
• Experience in building and launching APIs through BERT-based natural language fine-tuning and model optimization would be great.
• Experience in operating services in a Docker container-based environment would be even better.
• Understanding of quantization and experience applying it in learning/inference would be great.
• High understanding of PEFT techniques such as Prefix Tuning, Adapter, and LoRA would be great.
• Experience in keeping up with the latest LLM papers and applying SOTA algorithms would be great.
• Candidates with a Master’s degree or higher in natural language processing or experience participating in related field papers would be great.
[Joining Journey]
• Document review ＞ Online job interview ＞ Offline culture fit interview ＞ Salary negotiation ＞ Offer and joining
Benefits and Work Environment
• Flexible working environment
• Basic 4 major insurance
• Coffee, various teas, and snacks provided
• Development environment, cloud, and GPU provided
• Support for attending various seminars and conferences
• Book purchase support
Document screening - 1st (Technical) interview - 2nd Culture fit interview - Salary negotiation - Confirmation of joining
• If there are discrepancies or false information in the application documents, the hiring confirmation may be canceled.
• The basic probation period is 3 months, and the treatment after the probation evaluation will be discussed mutually.
• There should be no disqualifications for overseas travel.
• Company location: 61, Namhyeon 3-gil, Gwanak-gu, Seoul, Room 101
