---
title: 'Member of Technical Staff (Post Training) at Inherent'
canonical: 'https://feeny.ai/job/member-of-technical-staff-post-training-inherent-london-ksabd1ackh3b'
type: 'job'
last_seen: '2026-09-10'
---

# Member of Technical Staff (Post Training) at Inherent

- **Company:** Inherent
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-28
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/inherent/74a17da6-0a84-47ab-83d9-b4c122516407

## Job description

Member of Technical Staff, Post-Training — Inherent (London) At Inherent, we are on a mission to build AI that recursively self-improves to discover new knowledge. Scientific advances are the backbone of our economic, technological and societal prosperity, but ideas are getting harder to find and breakthroughs are becoming more expensive. We are building a new frontier lab dedicated to developing AI that explores “unknown unknowns” to uncover paradigm-shifting research contributions. Science is a social endeavour, and so our mission is inextricably a human-machine teaming problem. We’re starting by reinventing the AI research factory so that our own agents accelerate their own creation. Inherent is a well-funded, fast-growing neo-lab backed by Tier 1 VCs who believe in our ethical stance. We are a team of operators with backgrounds at frontier labs who have done foundational work in recursive self-improvement, AI Scientists, world modelling, meta-RL and human-machine cooperation. Working in-person every day at our high-intensity London headquarters, we believe that Europe will lead the way in the coming paradigm of AI-enabled science, unlocking human potential across the globe.

## About the role

We’re looking for Members of Technical Staff to lead work on post-training state-of-the-art foundation models for open-ended agentic capabilities in scientific research. You’ll be involved at every level of the post-training pipeline: sourcing and creating data, building autocurricula, devising and implementing SFT and RL algorithms, constructing tools and harnesses for foundation model self-improvement, analysing research results, and using information gained to devise future hypotheses. You will work closely with an experienced technical team of humans, and increasingly alongside the AI scientist collaborators we dogfood.

## What you'd do

- Design, implement, and tune SFT and RL algorithms to post-train models that autonomously perform state-of-the-art research.
- Build the autocurricula, judges, harnesses and eval pipelines that turn open-ended research tasks into reliable reward signal.
- Run large-scale experiments on state-of-the-art hardware and analyse experiments to determine the next hypotheses to test, in collaboration with our AI agents.
- Close recursive loops so that AI agents drive their own post-training research.
- Work closely with colleagues in the Infrastructure and AI for Science teams to optimise hardware and deliver remarkable performance in real scientific domains.

## What we're looking for

- 3+ years of deep learning research experience.
- Experience post-training large language, vision, video or multi-modal models.
- Demonstrated track record of success in deep learning research, whether papers, model releases, open-source contributions, or other artifacts.
- 5+ years of software engineering experience, including deep familiarity with Python and at least one deep learning framework (e.g., PyTorch, JAX).
- Experience using the latest coding agents, and opinions about optimal workflow.
- Enthusiasm for experimental organizational design.
- AI-pilled: adopting agents, keen to build a company where agents are front and centre.

Strong candidates may also have

- PhD in mathematics, computer science or hard science discipline.
- Hands-on experience training LLMs with RL at scale (GRPO/PPO, DPO, distillation, and variants).
- Familiarity with distributed and long-context training infrastructure.
- A background in autocurricula, open-endedness, meta-learning, or recursive self-improvement.
- Experience post-training frontier models at an industry lab (scale, infra, and iteration speed).

## Why this is interesting

- You'll shape the core research of a frontier AI lab from the beginning.
- You'll work on genuine recursive self-improvement — training AI scientists that improve the very pipeline that trains them — not incremental benchmark-chasing.
- You'll dogfood your own work: the agents you post-train accelerate the research that creates them.
- Small team, high trust, no bureaucracy, and a genuinely technical culture.

Culture If you believe in our mission and culture, and are qualified and motivated, we encourage you to apply, even if you don’t meet every one of the criteria above. We know that many of the most creative and talented people have had unusual career paths and backgrounds. Building a team with a diversity of thought is mission-critical, for plurality spurs curiosity, invention and collective experimentation.

## About Inherent

## Company Overview
- **One-liner**: Inherent is a London-based frontier AI lab building Faraday, an AI system for open-ended scientific discovery where humans and self-improving AI collaborate to tackle hard problems in science.
- **Entity Type**: Private (Seed stage; raised $50M)
- **Headquarters**: London, United Kingdom
- **Founded**: 2026 (public emergence from stealth)
- **Founders**: Tantum Collins, Edward Hughes, Louis Kirsch, Kaloyan Aleksiev

## Core Business
- Primary industry: Artificial intelligence for scientific research
- Target customers: R&D teams across global industries (B2B)
- Mission: “To discover new knowledge” by building AI-native research organisations that recursively self-improve

## Products & Services
- **[Faraday]**: An AI system designed for open-ended scientific discovery, enabling humans and self-improving AI to work together. It is not just an answer engine but a system that helps elucidate which questions to ask, accelerating research across domains and powering next-generation autonomous labs.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding of $50M (Seed round, May 2026)
- **Notable Investors/Partners**: Index Ventures (co-lead), Radical Ventures (co-lead); advisor Matt Clifford (co-founder of Entrepreneurs First)
- **Growth Signals**: Emerged from stealth in May 2026; actively hiring for 6 technical roles (Post Training, AI for Science, Factory Redesign, Infrastructure Engineering); headcount of 8 as of May 2026; strong founding team from DeepMind, Microsoft, and White House AI policy

## Competitive Advantages
- **Recursive Self-Improvement (RSI)**: Inherent applies RSI at the organisational level, not just to an individual AI agent, creating a feedback loop that continuously expands collective human-machine capabilities.
- **AI-Native Organisation Design**: The company is built from scratch around human-AI teaming, with a Public Benefit Corporation structure and a societal-benefit board to ensure ethical alignment.
- **Founding Team**: Co-founders with deep experience at DeepMind, Microsoft, and White House AI policy, giving credibility and access to top talent.

## Strategic Focus
- Write the “playbook for AI-native science” by reinventing the scientific method from first principles.
- Expand Faraday’s capabilities to enable autonomous labs and accelerate discovery across biology, chemistry, materials, and other hard sciences.
- Grow the team across research, engineering, and infrastructure while maintaining a culture of “living within the experiment.”

## Why Work Here
- **Culture**: “Living within the experiment” – the team builds and uses its own systems, ensuring alignment with human values and joy of discovery.
- **Mission-Driven**: Focus on open-ended scientific discovery and societal benefit, not narrow commercial metrics.
- **Early-Stage Impact**: Join as a member of technical staff in a seed-stage startup with significant autonomy and influence.
- **Location & Flexibility**: All current roles are based in London; remote/hybrid policy not explicitly stated but likely office-first given the collaborative nature of the work.
- **Notable Perks**: Opportunity to work on frontier AI research with ex-DeepMind researchers; contribute to a new paradigm for scientific discovery.

## Sources
1. [inherentlabs.ai](https://inherentlabs.ai/)
2. [tech.eu](https://tech.eu/2026/05/29/london-based-ai-lab-inherent-emerges-from-stealth-with-50m-raise/)
3. [fastaijobs.com](https://www.fastaijobs.com/companies/inherent)
4. [tracxn.com](https://tracxn.com/d/companies/inherentlabsai/__tzwS3n1lcCiPRxg_FWUxJKE0h7lWY9ir0PCL9cRg3p4)
5. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/inherent/8ae679ae-b8f0-4372-a23c-fedeb6c23bbc)

## Other roles at Inherent

- [Research Fellow: Winter 2027](https://feeny.ai/job/research-fellow-winter-2027-inherent-london-8vczd1xcyndx) — London, United Kingdom
- [Member of Technical Staff (Infrastructure Engineer, Training and Inference Systems)](https://feeny.ai/job/member-of-technical-staff-infrastructure-engineer-training-and-inference-y5v6edh52ps3) — London, United Kingdom
- [Member of Technical Staff (Infrastructure Engineer, Compute Infrastructure)](https://feeny.ai/job/member-of-technical-staff-infrastructure-engineer-compute-infrastructure-a5fv3911md6h) — London, United Kingdom
- [Member of Technical Staff (Factory Redesign)](https://feeny.ai/job/member-of-technical-staff-factory-redesign-inherent-london-wks460szjpa4) — London, United Kingdom
- [Member of Technical Staff (AI for Science)](https://feeny.ai/job/member-of-technical-staff-ai-for-science-inherent-london-wa3hjgm2zxg3) — London, United Kingdom