RLWRLD is a leading Physical AI company developing a Robotics Foundation Model (RFM) that enables robots to perceive, reason, and act in the real world like humans.
Building on deep research capabilities in AI and robotics and a strong data collaboration network with industrial partners in Japan, Korea, and beyond, RLWRLD is rapidly advancing our RFM to enable precise manipulation by high-degree-of-freedom robotic hands. The company is also collaborating with world-class research groups and partners in robotics and sensor solutions to develop AI models that can be practically deployed across industries such as manufacturing, logistics, and services.
Having raised approximately KRW 60 billion in cumulative seed funding from leading domestic and global venture capital firms and major corporations, RLWRLD continues to attract exceptional talent who are eager to drive innovation across AI, robotics technology, and business.
Position Overview
A Forward Deployed ML Engineer (FDML) is responsible for applying RLWRLD’s RFM (Robotics Foundation Model) and global Robot Foundation Models to real-world industrial environments. This role focuses on building data-driven inference environments on-site, fine-tuning, domain adaptation, and performance optimization.
This is not a pure research or model development role. It is a deployment-focused position, ensuring that ML-driven robotic behaviors—spanning data → model → control—operate reliably in real production environments.
As a member of the Robotics Deployment (RD) team, the FDML works closely with project managers and Robotics/AI teams to lead end-to-end ML deployment, covering the full lifecycle from PoC → data collection → model improvement → scaling → production (commercial operation).
Key Responsibilites
- Perform fine-tuning and domain adaptation tailored to industrial environments
- Deploy and stabilize models with a focus on inference and control performance optimization
- Quantitatively evaluate AI model performance and operate data quality and feedback loops
- Design and execute data collection strategies based on customer environments
- Clean data and build training datasets in collaboration with internal ML teams
- Build and support model operation infrastructure for customers and partners
- Translate on-site requirements into data-driven insights for model teams
- Structure ambiguous problems and convert them into actionable execution plans
Required Qualifications
- 3+ years of hands-on experience applying or operating ML in real-world AI/Robotics or Edge/Robotics environments
- Experience with ML frameworks such as PyTorch, TensorFlow, or JAX, including fine-tuning and inference
- Understanding of VLM, VLA, or Robotics AI (e.g., Imitation Learning)
- Experience designing, validating, and operating end-to-end ML pipelines from data → model → control
- Strong log analysis and data-driven problem-solving skills
- Experience collaborating and communicating technically with customers and SI partners
- Ability to independently define problems and drive solutions through execution
- Adaptive execution skills to structure problems and deliver results across diverse environments
Preferred Qualifications
- Experience developing ML/inference systems using Linux, Python, and C++
- Experience with robotics-related computer vision projects such as object detection and 6D pose estimation
- Experience building MLOps pipelines using Docker and Kubernetes
- Experience with ML projects based on industrial automation or robotics data
- Business-level communication skills in English or Japanese
- End-to-end experience or strong interest in Data → Model → Operation workflows
Working Conditions
- Work Location: 561 Seolleung-ro, Gangnam-gu, Seoul (RUBINA Building, Yeoksam-dong)
- Employment Type: Full-time
- Probationary Period
- A three-month probationary period will apply upon employment.
- During this period, your work attitude and performance will be evaluated.
- Depending on the evaluation results, the probationary period may be extended or the employment offer may be withdrawn.
How to Apply
- Application Materials:
- Resume in English or Korean
- (optional) Portfolio, research materials, or project documents showcasing your capabilities
- Application Deadline: Rolling basis
Hiring Process
- Document Screening → Coding Test → 1st Interview → 2nd Interview → 3rd Interview → Final Offer
- Candidates who pass the document screening will be contacted individually.
- Additional interview rounds may be conducted if necessary.
Benefits & Perks
- Flexible Work Schedule: Adjust your working hours autonomously to match your personal rhythm.
- Equipment & Software Support: We provide job-specific equipment and essential software required for your role.
- Office Amenities: Enjoy our in-office snack bar and coffee machines.
- Holiday & Birthday Gifts: Small gifts are provided for holidays and birthdays.
- Health Checkup Support: We support your well-being through regular health checkups.
RLWRLD is a leading Physical AI company developing a Robotics Foundation Model (RFM) that enables robots to perceive, reason, and act in the real world like humans.
Building on deep research capabilities in AI and robotics and a strong data collaboration network with industrial partners in Japan, Korea, and beyond, RLWRLD is rapidly advancing our RFM to enable precise manipulation by high-degree-of-freedom robotic hands. The company is also collaborating with world-class research groups and partners in robotics and sensor solutions to develop AI models that can be practically deployed across industries such as manufacturing, logistics, and services.
Having raised approximately KRW 60 billion in cumulative seed funding from leading domestic and global venture capital firms and major corporations, RLWRLD continues to attract exceptional talent who are eager to drive innovation across AI, robotics technology, and business.
Position Overview
A Forward Deployed ML Engineer (FDML) is responsible for applying RLWRLD’s RFM (Robotics Foundation Model) and global Robot Foundation Models to real-world industrial environments. This role focuses on building data-driven inference environments on-site, fine-tuning, domain adaptation, and performance optimization.
This is not a pure research or model development role. It is a deployment-focused position, ensuring that ML-driven robotic behaviors—spanning data → model → control—operate reliably in real production environments.
As a member of the Robotics Deployment (RD) team, the FDML works closely with project managers and Robotics/AI teams to lead end-to-end ML deployment, covering the full lifecycle from PoC → data collection → model improvement → scaling → production (commercial operation).
Key Responsibilites
- Perform fine-tuning and domain adaptation tailored to industrial environments
- Deploy and stabilize models with a focus on inference and control performance optimization
- Quantitatively evaluate AI model performance and operate data quality and feedback loops
- Design and execute data collection strategies based on customer environments
- Clean data and build training datasets in collaboration with internal ML teams
- Build and support model operation infrastructure for customers and partners
- Translate on-site requirements into data-driven insights for model teams
- Structure ambiguous problems and convert them into actionable execution plans
Required Qualifications
- 3+ years of hands-on experience applying or operating ML in real-world AI/Robotics or Edge/Robotics environments
- Experience with ML frameworks such as PyTorch, TensorFlow, or JAX, including fine-tuning and inference
- Understanding of VLM, VLA, or Robotics AI (e.g., Imitation Learning)
- Experience designing, validating, and operating end-to-end ML pipelines from data → model → control
- Strong log analysis and data-driven problem-solving skills
- Experience collaborating and communicating technically with customers and SI partners
- Ability to independently define problems and drive solutions through execution
- Adaptive execution skills to structure problems and deliver results across diverse environments
Preferred Qualifications
- Experience developing ML/inference systems using Linux, Python, and C++
- Experience with robotics-related computer vision projects such as object detection and 6D pose estimation
- Experience building MLOps pipelines using Docker and Kubernetes
- Experience with ML projects based on industrial automation or robotics data
- Business-level communication skills in English or Japanese
- End-to-end experience or strong interest in Data → Model → Operation workflows
Working Conditions
- Work Location: 561 Seolleung-ro, Gangnam-gu, Seoul (RUBINA Building, Yeoksam-dong)
- Employment Type: Full-time
- Probationary Period
- A three-month probationary period will apply upon employment.
- During this period, your work attitude and performance will be evaluated.
- Depending on the evaluation results, the probationary period may be extended or the employment offer may be withdrawn.
How to Apply
- Application Materials:
- Resume in English or Korean
- (optional) Portfolio, research materials, or project documents showcasing your capabilities
- Application Deadline: Rolling basis
Hiring Process
- Document Screening → Coding Test → 1st Interview → 2nd Interview → 3rd Interview → Final Offer
- Candidates who pass the document screening will be contacted individually.
- Additional interview rounds may be conducted if necessary.
Benefits & Perks
- Flexible Work Schedule: Adjust your working hours autonomously to match your personal rhythm.
- Equipment & Software Support: We provide job-specific equipment and essential software required for your role.
- Office Amenities: Enjoy our in-office snack bar and coffee machines.
- Holiday & Birthday Gifts: Small gifts are provided for holidays and birthdays.
- Health Checkup Support: We support your well-being through regular health checkups.