AI-Native HR Problem Finder; MPC Project

Our MPC project runs three blockchain and crypto businesses, each with its own team. Projects like this rarely struggle because of the technology. They struggle because of people: the right hires don't arrive in time, teams wait on each other, good people leave, and nobody can say which of these is actually costing the business. We need the person who finds that problem and proves it.

This isn't an HR generalist, recruiter or HR admin role. You'll focus only on the people problems inside the MPC project and its three teams. You'll find where the business loses money, time or talent today, prove it with data, and hand the team a clear brief they can act on. You'll judge your work by one thing: whether the problems you chose helped MPC succeed.

MUST Company is based in South Korea. We build AI products, Web3 tools for real-world assets, and Match Hire, the hiring platform this job is posted on. Our team works remotely across Asia and Africa. MPC is our blockchain and crypto project: a set of businesses covering crypto mining, digital-asset trading and blockchain products. Its teams move fast, and hiring the wrong person, or hiring too late, costs real money.

We don't hire people to follow instructions. Everyone here owns their area, makes calls and answers for the results. If you spot a problem, even outside your role, we expect you to raise it and suggest a fix. You'll work directly with the founders and the MPC team leads, so decisions happen quickly.

We use AI every day for research, writing and analysis, but people are still responsible for the judgment. Most of our communication is written, and we care about what you get done, not when you're online.

• Find the people problems that hold MPC back: roles that stay open too long or get filled with the wrong person, teams missing key skills or stretched too thin, work that stalls between teams, people leaving or not performing, and onboarding that is too slow for a fast-moving crypto business.
• Prove each problem with evidence: hiring funnel data, time-to-hire, team capacity and output, attendance, review results, turnover and exit reasons, and real conversations with MPC team leads, members and candidates.
• Connect each people problem to a business result. Show what a missing hire, a skills gap or a turnover problem costs MPC in revenue, speed or risk.
• Rank problems by business impact, cost, urgency and how easy they are to fix, and pick the one worth solving first.
• Write a short, clear brief for each chosen problem: which team has it, what it costs today, what we'd change, and what success looks like.
• Turn the brief into a prioritized task list with acceptance criteria for the HR team, for the team leads, or for engineering when the fix belongs in our HR systems or AI agents.
• Define the right people and skills profile for each MPC team (blockchain, crypto, trading and business development talent) so hiring targets the right people.
• Use AI tools and agents to research and analyze faster and deeper than one person could by hand.
• After a fix ships, measure whether it worked and feed what you learn into the next problem.

In the first month, you'll learn MPC's three businesses, talk to the founders, team leads and members, and deliver the top 3 people problems across MPC ranked by business impact, backed by real data and at least 10 conversations.

By the end of the second month, one problem should be chosen with a written business case, and the team should be working from your prioritized task list.

By the end of the third month, we'd like to see the first measurable result for MPC (a critical role filled, a team gap closed, better retention or faster onboarding) and a weekly report on the KPIs…