Skills

Python Research Training Architecture Machine Learning PyTorch

Job Specifications

Member of Technical Staff (Applied ML) – Agentic AI

London, UK - Hybrid / Flexible (must be UK-based already | £200k+ & Equity

A new frontier in AI infrastructure is being built, and we’re hiring the founding technical team to make it happen.

Mission: to create super-intelligence as a copilot for AI teams. A system that enables enterprises to move from experimentation to full-scale production without the need for a massive ML engineering organisation.

An early-stage, high-impact startup founded by engineers and researchers from Google, Spotify, and Uber, backed by some of the world’s most influential investors. With offices in London and San Francisco, they’ve just completed a major funding round and are scaling toward Series A in early 2026.

The Role

We’re looking for a Member of Technical Staff (Applied ML) who thrives on building systems that work in the real world.

You’ll join as one of the company’s first 10 engineering hires, shaping the core architecture, training stack, and intelligent agent frameworks that define how AI systems reason, plan, and act autonomously.

This is not a research-only position; it’s a hands-on, product-focused role where execution speed and technical depth matter.

What You’ll Do

Design and implement large-scale agentic AI systems and intelligent orchestration layers.
Work across the stack, from data pipelines to model deployment and real-time inference.
Build tools and infrastructure that empower ML teams to deploy and iterate faster.
Collaborate directly with founders on architecture, strategy, and product roadmap.
Contribute to a high-performance, low-ego engineering culture focused on shipping.

What We’re Looking For

Deep experience in Applied Machine Learning and Agentic AI systems.
Proficiency in modern ML stacks (Python, PyTorch, JAX, Ray, etc.) and production deployment.
Proven ability to move fast, ship code, and bridge research with real-world impact.
Experience in early-stage or startup environments is a plus.
A “builder” mindset; you’re happiest when ideas turn into working systems.

Key Experience:

Agentic System Design
LLM Engineering/Foundation Models
Planning and Reasoning
Scalable ML Infrastructure
Reinforcement Learning (esp. RLHF/RLAIF)
Simulation or feedback-driven adaptation

Interview Process

Initial Chat – Conversation with a Founder
Technical Round 1 – Agentic System Design
Technical Round 2 – Engineering Principles
Final – Meet the Co-Founders

If you want to help define how the next generation of AI systems think and act, this is your chance to join early, build fast, and have a tangible impact.

About the Company

We believe that advanced technology is paving the way to a more sustainable future. We believe in going the extra mile to provide our customers with a competitive edge. Since our inception in 2010, Cubiq has established a reputation for excellence in the delivery of high quality engineering talent to the most ground-breaking technology companies in the world. Cubiq methods are subtle, data-driven, and highly effective, which is how we have become widely recognised as leading experts within engineering and technology recr... Know more