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Open jobs9
NEW · 7D+0
Top hiring locationSeoul, Korea | 대한민국 서울특별시 서초구 강남대로 343
Last checkedNov 1, 2026
HIRING TELEMETRY · CURRENT OBSERVATION
Read current hiring through measured values
01CURRENT HIRING
9Open jobs
DIRECT0
ADJACENT9
NEW · 7D+0
This is the current job count. It does not by itself establish hiring expansion, contraction or company growth.
02ANALYSIS COVERAGE
This company's postings have not been analyzed yet. Only the current job count and observation time are shown.
03OBSERVATION WINDOW
37DObserved window
Monitoring startedSep 24, 2026
Latest observedNov 1, 2026
COMPARABLE HISTORICAL TRENDNOT YET AVAILABLE
NEW · 7D jobs: 0 How to read confirmed / not confirmed / NEW · 7D
Confirmed means directly stated in current postings. Not confirmed means the item has not been verified in the postings reviewed. NEW · 7D means first observed by Banseog within the last seven days.
WHAT THEY ARE HIRING FOR
Start with your role
CURRENT OPEN JOBS
Current jobs you can inspect now
Field & Integration[Infra] Field Engineer (세종)마키나락스 세종오피스 | Sejong, Korea
Official apply ↗Field & Integration[Infra] Field Engineer마키나락스 | 대한민국 서울특별시 서초구 강남대로 343
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer Lead (창원)Country unconfirmed
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer - Vision(Defect Detction)Seoul, Korea | 대한민국 서울특별시 서초구 강남대로 343
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer - LLM QuantizationSeoul, Korea | 대한민국 서울특별시 서초구 강남대로 343
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer - LLM [Tokyo, JP]Tokyo, Japan | 1-chōme-17-1 Toranomon, Minato City, Tokyo 105-6415 일본 | 도쿄 도라노몬 CIC Tokyo 내 마키나락스 오피스
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer - LLM (창원)Country unconfirmed
Official apply ↗Field & Integration[FDE] Forward Deployed Engineer - LLMSeoul, Korea | 대한민국 서울특별시 서초구 강남대로 343
Official apply ↗Recurring work experience
Experience repeated in current postings
These are recurring work requirements or experience areas in current job postings.
BANSEOG OUTLOOK
On closed-network sites, the product team's most accurate sensor is the engineer back from the trip
MakinaRocks' AI operating system, Runway, was designed for closed-network (air-gapped) and on-premises settings in manufacturing and defense. In October 2026 it trialed an AI aboard the naval vessel Pohang, where outside network access is restricted, that finds manual content without the internet, and 27% of first-half orders came from defense and aerospace. With a service delivered over the internet, usage records build up straight away with the development team, but that is hard to do where the network is closed. Banseog reads this to mean that the more sensitive the customer, the less the material a product learns from comes back on its own. So Banseog sees the people and procedures that safely bring what was seen on site back into the product as the next talent challenge.
Questions before joining
- By what route do failures and usage records from closed-network sites get back to the product team?
- How is time split between site work and headquarters development, and what are the security procedures?
- Can you share a recent case where a problem found on site was reflected in the product?
The AI aboard the Pohang does not make decisions; it helps sailors find manual content. If use continues, a way to check which questions failed, within security procedures, may become important.
The company has explained that work done in the first half leads to customer acceptance in the second half. As deliveries bunch up, recording field knowledge in a set format rather than in people's memories may become a larger task.
On a long-running site, such as the forging project that runs through December 2029, a design that builds diagnostics into the product so customers can find problems themselves may become important. These are conditional stages, not confirmed dates or hiring plans.
Capabilities gaining importance
Bringing back field knowledge within security rulesDesigning closed-network installation, update and rollbackBuilding field diagnostic tools into the productRunning lightweight models on limited hardwareSeparating shared features from customer-specific settings
Talent markets to explore
Manufacturing AI and process dataAir-gapped and on-premises infrastructureAI platforms and MLOpsDie and forging process engineeringDefense and naval systems software
Current hiring comes from the existing verified data pipeline. This is a conditional talent and organization outlook, not a company hiring plan, personal-fit assessment or hiring-probability forecast. · 2026-11-01
FUTURE TALENT SHIFT
How responsibilities may expand
Follow the responsibility from implementation on site through safely sending that site's knowledge back into the product. Check individual postings for actual duties and qualifications.
Building and delivering models at customer sites→After returning, passing problems and solutions to the product in a form that can be reproduced
Developing Runway features→Building tools into the product that allow diagnosis without remote access
Handling installation in customer environments→Standardizing update and rollback procedures with no outside connection
Improving performance on customer data→Designing evaluation and model-slimming methods for when data cannot be brought out
Handling pre-delivery checks→Agreeing with customers on what information may leave the site
Collecting customer requests→Finding shared problems in infrequent field reports and setting priorities
CAREER LENS
Experience solving problems where you cannot see the logs
Look for work where you found a problem without remote access or enough logs, and work where you turned what you learned on site into something the team could keep. Adjacent experience suggests connections, not eligibility or a personal-fit verdict.
Experience to show in your career history
✓
Installing and updating software in an environment cut off from the internet
✓
Finding the cause of a failure in a customer environment where logs could not be brought out
✓
Turning a field solution into a product feature or a document
✓
Getting a system into a customer environment through a security review
✓
Slimming down an AI model and running it on limited hardware
✓
Defining a problem together with site staff at places such as factories or vessels
Where adjacent experience can lead
Putting systems into separated networks and running them can connect to Runway deployment.
The connection is building models from factory data and applying them to lines.
Experience carrying out delivery and testing within security procedures.
Look at experience organizing field problems into cases that can be reproduced.
Experience running models on limited hardware.
Building tools that let users find problems themselves can connect to diagnostics built into the product.
Questions before joining
- By what route do failures and usage records from closed-network sites get back to the product team?
- How is time split between site work and headquarters development, and what are the security procedures?
- Can you share a recent case where a problem found on site was reflected in the product?
- Which of defense, heavy industry, advanced manufacturing and general manufacturing does this role cover?
- Are there security requirements for taking part in defense projects?
PLACE × TALENT INTELLIGENCE
Work connected across locations
These interpretations use publicly reported business and trial activities. They do not describe regional hiring plans or current staffing.
The company has its headquarters in Seoul. This reads as the point where experience from many sites gathers into a shared product, without presuming current team structure or headcount.
Runway developmentAI agentsProduct standards
This is the setting for a hot-forging project that runs through December 2029. It reads as a place to learn the standards of skilled work by staying on site for a long time, without presuming research results.
Die design correctionProcess controlQuality inspection
A trial that helps crew find manuals and maintenance materials aboard a vessel where outside network access is restricted. The AI does not decide how equipment is operated, and the procedure for bringing back actual records has not been disclosed.
On-device AIClosed-network operationDocument evidence control
Major customers the company has named include Doosan Enerbility, Samsung Electronics and Hyundai Motor. How customer site needs get back into the product remains a separate thing to confirm.
Site dataDeployment designRequirements
Closed-network site → engineer's return report → reflected in the product → built-in diagnostics → faster installation at the next site