Technical Recruiter (12 Month FTC) - DeepTech, AI Research Lab

Location: London or Cambridge

Working style: Hybrid - 3 days a week in office

Salary: Up to £90k

Contract: 12-month FTC.

Hawkwood are partnering with a pioneering deep-tech start-up who are at the forefront of AI-driven materials discovery. Our client is advancing artificial intelligence to push the boundaries of science and technology, with applications spanning across climate-tech, advanced manufacturing, clean energy and other areas where breakthroughs can deliver meaningful environmental impact.

Founded by a world-renowned AI Professor and a deep-tech commercial leader, the business combines scientific pedigree with proven execution. The team includes some of the most cited AI and science researchers globally, operating within a high-performance culture defined by ambition, technical excellence, and real-world impact.

Following a landmark $100m funding round led by a Tier One US VC firm and NVIDIA, our client is set to intentionally scale by ~45 heads over the next 12 months. As such, they are seeking a Talent Partner to support with this growth. This is a rare opportunity to be part of a mission-driven organisation using AI to solve some of the most complex environmental challenges.

About the role:

Due to critical growth phases in our R&D roadmap, we are looking for a Talent Partner to join on an initial 12-month Fixed Term Contract to lead the identification and acquisition of elite technical and scientific talent.

What you'll do:

• Own the end-to-end recruiting process for high-priority technical roles, ranging from Machine Learning Engineers and Research Scientists to Computational Chemists and Lab Automation Specialists.
• Develop creative sourcing strategies to identify and engage passive talent from top-tier research labs, tech giants, and academic institutions.
• Collaborate closely with Hiring Managers to draft compelling job descriptions, define assessment criteria, and calibrate role requirements.
• Organise and run interviewer calibration sessions to ensure understanding and alignment around the focus areas for each interview stage and assist with the creation/refinement of appropriate questions and/or tasks.
• Act as a talent advisor, providing market insights on compensation, talent availability, and hiring trends within the Deep Tech and AI landscape.
• Execute a high-touch, seamless candidate experience that reflects the businesses values, with the goal that every applicant - regardless of the outcome – becomes an advocate.
• Maintain rigorous data hygiene within the ATS (Ashby), ensuring pipeline visibility and enabling data-driven hiring decisions.
• Uphold expected service levels around critical tasks, such as reviewing applications, responding to referrals, conducting screening calls, scheduling interviews, writing up feedback, replying to candidate requests, updating stakeholders, etc.
• Potentially help to represent the business at certain industry events, conferences, and/or meetups to build a long-term network of talent in the AI and Materials Science domains.

What we're looking for:

• You are comfortable joining on a 12-month FTC basis.
• Experience & Context: You have significant experience (mid-to-senior level) in fast-paced full-cycle recruitment, ideally within a start-up or scale-up environment or a specialised technical search firm.
• Adaptability & Curiosity: You look to understand the "why" behind each new role, building trust with hiring teams by asking questions and doing your own research to get below the surface of the JD.
• Technical Fluency: You possess a strong track record of hiring for complex technical profiles. You effectively understand the nuances between different engineering and research disciplines (e.g. Machine Learning, MLOps, Software Engineering, etc.) and can credibly screen candidates for different types of roles based on technical requirements.
• Ideally, you have experience recruiting for Deep Tech scientific research organisations.
• Ideally, you have a pre-existing network of candidates in the Generative AI, Deep Learning, or Computational Chemistry spaces.

Next steps:

If you are interested in this opportunity, we kindly request that you apply via this LinkedIn advert, as opposed to sending us an email or a LinkedIn direct message. We are eager to ensure that each candidate application is considered fairly and receives a consistent experience. Unfortunately, we cannot ensure this standard if you enquire about a role via email or LinkedIn message, as it falls outside of our established process.