Forward-Deployed Engineer

The Role

Config is building the data and model layer for real-world robotic automation. We develop scalable data infrastructure and robot foundation models for bimanual manipulation, helping customers automate complex physical tasks faster.

We are already working with multiple enterprise customers, including Fortune Global 500 companies, to bring robot foundation models from research into real-world production environments.

As a Forward-Deployed Engineer, you will own the customer-side adaptation loop: understanding the customer's target task, designing the data strategy, deploying data collection and evaluation pipelines, driving model adaptation, analyzing failure modes, and rapidly iterating until Config's models are successfully adapted to real-world customer workflows.

This is a high-ownership role at the intersection of robotics, machine learning, product, and customer deployment. You will work closely with Product, Technology teams, and customers to turn complex automation challenges into repeatable, scalable robotic intelligence.

** This JD is designed to cover multiple levels.

Level: We are open to candidates from interns to senior, staff, and senior staff professionals. Level, scope, ownership, and compensation will be calibrated based on experience.

When applying, please specify the level that best reflects your experience and interests. We're happy to calibrate scope and leveling throughout the interview process.

Areas You May Contribute To

• Work directly with Product, Technology teams, and customers to turn target tasks in real customer operating environments into successful robotic automation deployments.
• Build and extend the software that integrates Config's Loop platform with each customer's robots, sensors, and systems — including customer-facing SDKs and integration interfaces.
• Build tools, scripts, and workflows that make customer deployments faster, more reliable, and more repeatable.
• Own the customer model adaptation loop: run or coordinate task-specific data collection, model fine-tuning/adaptation, and evaluation — identifying key failure modes across data, sensing, model training/inference, system integration, and iterating through to redeployment.
• Design task-adaptation data strategies for customer's use-case, including scenario coverage, variation design, failure case discovery, and data collection protocols.
• Support on-site deployment at customer sites — setting up robots, sensors, and Config's collection/evaluation pipelines and getting them running in the field.
• Communicate technical findings clearly to Product, Technology, and customer stakeholders.

What We're Looking For

• Strong engineering ability, especially in Python and robotics/ML-related systems.
• Experience building and shipping software in real-world deployment or customer-facing environments — integrating hardware, sensors, data, and models end to end.
• Strong ownership, product sense, and ability to operate in customer-facing technical environments.
• Ability to debug complex issues across software, hardware, data, and model behavior.
• Comfort working in fast-moving, ambiguous environments.
• Excitement about turning robot foundation models into real-world automation systems.
• Excellent communication and collaboration skills in Korean and written English.

For senior-level candidates, we typically look for 5+ years of relevant research or engineering experience, or equivalent evidence of exceptional technical ownership. For staff and senior staff-level candidates, we look for a stronger track record of independently defining technical direction, driving ambiguous projects, mentoring others, and delivering high-impact systems or research outcomes.

Bonus Points

• Experience with robot learning, imitation learning, teleoperation, VLA/RFM systems, or model fine-tuning.
• Experience with robot arms, grippers, cameras, sensors, calibration, or on-site robotics deployment.
• Experience with Docker, cloud infrastructure, data platforms, or deployment automation.
• Prior startup experience or experience in a high-ownership technical role.
• Prior experience in fast-moving startup or research-driven engineering environments.