Model ML

AI Workspace for Financial Services.

Location: London

Company Overview

Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever. The round was backed by FT Partners, Y Combinator, LocalGlobe, QED, 13books, and other top global investors, bringing total funding to $90 million.

The Role

This is a company-level leverage role.

You will work directly with the founders to build the systems, operating rhythms, and information infrastructure that allow Model ML to scale without losing speed, clarity, or execution quality.

Your job is not to manage projects. Your job is to ensure the company sees clearly and executes intelligently.

You will operate across product, GTM, engagements, data, hiring, and internal operations. One hour may be spent in an engineering prioritisation discussion. The next in a customer escalation. The next redesigning how leadership reviews company performance.

The common thread is leverage.

You should naturally think in systems, resource allocation, operating cadence, and decision velocity. You should be comfortable identifying where information breaks down, where time is being wasted, and where leadership attention is misallocated.

This role is best suited for someone who wants to become a world-class company builder, not a functional specialist.

What You’ll Be Responsible For

• Build and own the company operating system. Leadership cadence, planning cycles, KPI infrastructure, resource allocation, and execution reviews.
• Ensure the CEO and leadership team can access critical company information quickly and reliably. What matters should be obvious. What is blocked should be visible.
• Design decision infrastructure across the company. Dashboards, reporting systems, review frameworks, escalation paths, and operational feedback loops.
• Identify where resources and attention are misallocated across GTM, engagements, engineering, and data. Redirect focus aggressively when priorities drift.
• Convert ambiguity into execution clarity. Create operating plans with clear ownership, sequencing, and measurable outcomes.
• Monitor customer signals across trials, deployments, expansion opportunities, support issues, and engagement patterns. Ensure important signals reach the right teams quickly.
• Partner closely with Data and Engineering to build live operational intelligence systems across Looker, Redshift, internal tooling, and AI workflows.
• Improve operational velocity across the company. Remove friction across systems, meetings, workflows, approvals, and communication layers.
• Build frameworks that scale judgment. Hiring systems, review systems, calibration systems, and performance infrastructure.

What Success Looks Like

• Leadership meetings become decision environments, not status updates.
• Critical customer and product signals move through the company quickly.
• Teams operate with higher velocity and less ambiguity.
• Important initiatives stop dying in cross-functional gaps.
• Leadership attention is consistently focused on the highest-leverage work.
• The company develops stronger operational clarity as it scales.

Who Tends To Succeed In This Role

The strongest candidates usually come from one of these paths:

A. Founder’s Office / Strategic Operator

Worked directly with a founder or executive team at a high-growth startup. Built internal systems, operating cadence, planning infrastructure, and cross-functional execution processes.

B. Consulting or Banking → Startup Operator

Started in consulting, investment banking, or another high-performance analytical environment. Left early to join a scaling startup and became deeply operational.

C. Product + Business Hybrid

Comfortable operating across technical and commercial environments. Can sit in an engineering standup, customer escalation, and leadership review in the same day.

D. Internal Systems Builder

Naturally creates structure in chaotic environments. Builds dashboards, operating frameworks, workflows, and decision systems without being asked.

What We’re Looking For

• Extremely high agency.
• Strong commercial instinct.
• Structured thinker with strong analytical depth.
• Comfortable challenging senior stakeholders when priorities drift.
• Obsessed with leverage, not activity.
• Strong written and verbal communication.
• Comfortable operating with ambiguity and incomplete information.
• Fast. Calm under pressure. Low ego.

You do not need experience in every function. But you do need the ability to understand how functions connect and where execution breaks down.

What You Can Expect

• Direct access to the founders and leadership team.
• Very high ownership from day one.
• Fast decision-making and minimal bureaucracy.
• Exposure to company-level strategy and execution.
• Intense pace and high standards.
• The opportunity to help build the operating system of one of the fastest-growing AI companies in financial services.