"Conquering cancer through AI"
Lunit, a portmanteau of ‘Learning unit,’ is a medical AI software company devoted to providing AI-powered total cancer care.
Our AI solutions help discover cancer and predict cancer treatment outcomes, achieving timely and individually-tailored cancer treatment.
🗨️ About the team
Who will I spend my day with?
- You will work in the cancer screening group of the AI research department, with a group of enthusiastic and talented AI researchers and engineers. We contribute to real-world products, while also solving meaningful and applied research projects.
- The teams and members of the department have diverse cultural backgrounds (5 nationalities!), experience, and interests.
- We have an open and free culture. Most people love to socialize and chat, but you are not expected to and are also free to opt-out.
How do they bond as a team?
- Our team fosters a friendly and open environment, encouraging idea-sharing and collaboration in research, engineering, and team events.
🗨️ About the position
What will make me proud to work here?
- You will be able to make a direct impact on our mission to conquer cancer through AI, by contributing to software that is used in real hospitals around the world.
- Your work will push forward our AI research frameworks, inference engines, and performance of the AI models. Lunit has best-in-class products thanks to these components.
- We have access to very large in-house labeled and unlabeled datasets and the cloud computing power to leverage them.
- Current projects span a variety of topics, including but not restricted to object detection, semantic segmentation, large-scale self-supervised learning, domain generalization, active learning, multi-task learning, ML pipelines, among others.
- We contribute back to the community through publications, blog posts, dataset releases, and the organization of public events such as machine learning challenges.
- Experience personal and professional growth by working on diverse projects and collaborating with talented multi-disciplinary teams.
🚩 Roles & Responsibilities
- Develop, and implement high-quality medical AI research frameworks, ML pipelines, and products for advancing healthcare.
- Contribute to large-scale and distributed inference engines.
- Enhance the maintainability, reliability, and efficiency of both new and existing AI software for various applications in cancer screening.
- Produce high-quality software by refactoring existing research frameworks or adopting new technologies and libraries
- Create innovative medical AI models by implementing or proposing cutting-edge methodologies and contributing to research projects.
- Collaborate closely with research scientists, engineers, and medical doctors on diverse real-world AI projects.
🚩 Tools Used
- Programming languages/framework: Python, PyTorch, MLFlow, Ray, Prefect
- Infrastructure: Google Cloud Platform
- General: Git, Docker, Confluence, Jira
Requirements
🎯 Qualifications
- 2+ years of professional experience in the IT industry
- Experience in machine learning engineering or research engineering in the AI industry
- Experience with Python, unit/integration testing, documentation, Git, collaborative code development, MLOps, and Docker
- Familiarity with machine learning frameworks and platforms(e.g., PyTorch, Tensorflow, MLFlow)
- Experience in bringing machine learning-based software to production
- B.Sc., M.Sc, or Ph.D. degree in computer science or a related field
- Keen eye and attention to detail
- Team player with experience working in teams with 3+ members
- Passion for machine learning engineering, research, and software engineering’s best practices
🏅 Preferred Experiences
- Experience with parallel, distributed, and cloud computing (e.g., GCP, AWS, or Azure)
- Experience with frameworks like TensorRT and openVINO
- Ability to communicate and write technical reports in English
- Contributions to open-source repositories in computer vision, machine
- Stimulate and push various initiatives within a team, e.g., code refactoring, dissemination of knowledge, culture-related events, etc
- Strong desire to have an impact in healthcare and conquer cancer through AI
📝How to Apply
- CV (resume, free format, in English)
🏃♀️ Hiring Process
- Document Screening → Introductory Interview → Assignment → Competency-based interview → Culture-fit Interview → Onboarding
- Competency interview Includes two parts:
- A short presentation describing the assignment
- Technical Interview
- All interviews are conducted in English
- After the final interview, we may proceed with reference checks if needed
- Competency interview Includes two parts:
🤝 Work Conditions and Environment
- Work type: Full-time
- Work location : Lunit HQ(5F, 374, Gangnam-daero, Gangnam-gu, Seoul)
- Salary: After negotiation
🎸 ETC
- If you misrepresent your experience or education or provide false or fraudulent information in or with your application, it may be grounds for cancellation of the employment.
- Lunit is committed in providing the preferential processing to those eligible for employment protection (national merits and people with disabilities) relevant to related laws and regulations.
Benefits
🌻 Benefits & Perk
The new office is one minute away by foot from Gangnam Station Exit 3 making it very convenient
Up to 12, 000 won is covered for both lunch and dinner when working at the office.
Up to 300,000 won is covered upon joining to decorate your personal workspace
Provide the latest computer models, such as Macs and 4K monitors, and renew them every three years
Attending seminars and purchasing books are covered
Regular in-house AI and medical seminars are held
Korean language education is provided for Lunitians who do not speak Korean as their first language
Access high-quality AI learning resources & deep learning DevOps system
Up to 1.2 million won worth of benefits points can be claimed annually
Korean National holiday gift: Seollal and Chuseok gift/voucher
Annual medical checkups and employee accident insurance are provided
Financial support for participation in employee gatherings (once a month)