Co Founder Position - Biotech

Robert Walters UK
London
1 year ago
Applications closed

Related Jobs

View all jobs

Artificial Intelligence Co-Founder / CCO (100 % remote) (m/f/d)

Junior / Graduate Data Scientist

Data Scientist

Data Scientist

Audio Machine Learning Engineer

Junior Data Scientist / Data Analyst

Are you an innovative leader passionate about blending machine learning and biotechnology to create transformative solutions? Are you ready to co-create and scale a biotech start-up poised to redefine protein yield engineering and strain engineering in a head of science / Co Founder position?

I am currently recruiting for a Co-Founder to help build a biotechnology business from the ground up.

This business is a biotech start-up with a mission to revolutionise synthetic biology by integrating cutting-edge machine learning with advanced biological engineering techniques. Their focus lies in solving complex challenges in protein yield optimisation and strain engineering for their clients.

I am recruiting a Co-Founder to shape the company’s technological direction and strategy. This is a unique opportunity to combine your technical expertise with entrepreneurial flair to build and grow an exciting biotech company.

Key Responsibilities

  • Lead the development and integration of machine learning approaches for protein engineering.
  • Design and oversee innovative experimental workflows to advance our core capabilities.
  • Work directly with external clients and partners to deliver tailored solutions and foster strategic relationships.
  • Recruit, develop, and manage a talented multidisciplinary team.
  • Identify opportunities for growth, secure partnerships, and assist with fundraising efforts.
  • Define and execute the company’s technological and biological roadmap in alignment with broader business goals.
  • Carry out business development duties from the earlier stages of the business to add to the current client list.

Requirements

  • Extensive experience applying ML to biological problems, particularly in protein and strain engineering.
  • Solid grounding in molecular biology, synthetic biology, or related fields.
  • Proven ability to work with clients and stakeholders to deliver impactful outcomes.
  • Experience in a start-up environment or demonstrated ability to thrive in fast-paced, high-growth settings.
  • Strong track record of building and managing diverse teams.
  • Familiarity with business development, funding processes, and commercialisation in biotech.

The role is offering a salary of up to £130,000 per annum, with a slightly reduced initial rate until seed funding is secured, alongside a sizeable equity package. This will be a hybrid role, with offices and labs based in London.

Please apply within if you are interested in hearing more.

About the job

Contract Type: FULL_TIME

Specialism: Information Technology

Focus: Data Science & AI Research

Workplace Type: Hybrid

Experience Level: Director

Location: London

J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.