Lead Technical Recruiter

Humanoid
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Geospatial Data Scientist

Senior Machine Learning Engineer

Product Manager AI (AI & Machine Learning)

Senior Machine Learning Engineer, Search & Recommendations

Consultant, Data Science and Business Analyst, AI & Data, Defence & Security

Data Scientist

At Humanoid we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.

In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries.

The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization.


As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed.

By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs.


Responsibilities:

- Lead the recruitment process for complex technical and business roles within the humanoid robotics division.

- Develop and implement effective recruiting strategies to attract high-caliber candidates from the global talent pool.

- Collaborate with hiring managers and executives to understand staffing needs and create detailed job descriptions.

- Source, screen, and interview candidates, ensuring a smooth and efficient hiring process.

- Manage the candidate pipeline and maintain relationships with potential candidates.

- Provide a positive candidate experience and ensure timely communication throughout the hiring process.

- Utilize various recruitment tools and platforms to enhance candidate sourcing and engagement.

- Stay updated on industry trends and best practices in recruitment and talent acquisition.


Expertise:

- Minimum of 5 years of experience in recruitment.

- Extensive experience in hiring for the robotics or technology sector is highly desirable.

- Demonstrated success in recruiting for international markets and navigating cross-cultural hiring challenges.

- Proficiency in English, both written and spoken, is essential. Additional language skills are a plus.

- Strong interpersonal and communication skills, with the ability to build relationships with candidates and hiring managers.

- Excellent organizational skills and the ability to manage multiple priorities in a fast-paced environment.

- Familiarity with applicant tracking systems (ATS) and other recruitment software.

- A proactive and results-oriented mindset, with the ability to work independently and as part of a team.


Benefits:

- High competitive salary.

- 23 calendar days of vacation per year.

- Flexible working hours.

- Opportunity to work on the latest technologies in AI/ML, Robotics and others.

- Startup model, offering a dynamic and innovative work environment

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.