500+ Hours Saved! Labellerr's Hiring Process For AI Roles

Have you ever spent hours applying to jobs, only to get stuck in a cycle of repetitive calls and generic interviews? You're not alone.

The hiring process today wastes too much time on introductions and tests that don't reflect real work.

At Labellerr, we take a different approach, one that values your skills, respects your time, and gives you a real preview of what working with us feels like.

Who We're Looking For?

• Founding engineers (interns or professionals with up to 3 years of experience).
• Velocity-driven innovators who thrive in AI-driven environments where speed matters.
• AI enthusiasts who explore new tools and tech out of curiosity, not just work assignments.
• Problem solvers who see coding as logic-building, not just memorizing syntax.
• Versatile builders who adapt to different languages and frameworks as needed.

If this sounds like you, our hiring process is designed with you in mind and you should continue reading further.

The Problem with Traditional Hiring

Let’s do the math:

• You apply to 500 jobs in a month.
• Each promising role starts with a 60-minute introduction call.
• That’s 500+ hours wasted repeating the same details.

Then, you face technical interviews that take another 1-2 hours per company, often testing abstract problems that have little connection to real-world work.

This process might work for large companies with HR teams, but for an early-stage startup like Labellerr, we believe there’s a smarter way to hire talent.

The Labellerr Solution: High-ROI Hiring

Our application process is designed with one core principle: maximize your return on invested time. Here's how we do it:

Stage 1: Smart Introduction - Resumes Are Too Generic

Instead of a long introductory call, we ask candidates to submit a cover letter that clearly explains their background, skills, and interests. This saves time and helps us understand their strengths quickly.

To make it even better, candidates can add a voice message to explain their experience. This lets us assess communication skills while keeping the process flexible.

What to Include in Your Cover Letter?

Your cover letter should answer these key questions:

1. Your Strengths

• What skills make you a strong candidate?
• Which tools, frameworks, or technologies do you specialize in?

2. Your Previous Work or Projects

• What important projects have you worked on?
• How did you contribute, and what problems did you solve?

3. The Role You’re Applying For & Why You Chose Us

• What position are you applying for?
• Why do you want to work at Labellerr? How does this role fit your career goals?

4. Why Should We Choose You?

• How do your skills and experience match this role?
• What value can you bring to the team?

By following this format, you can highlight your strengths clearly while helping us identify the right talent efficiently.

Stage 2: Real Problems, Not Puzzles

We don’t believe in asking you to solve random coding puzzles. Instead, we give you a real problem that we’re currently tackling at Labellerr.

Think of it as a compressed version of your first week on the job, a practical challenge that reflects the work you’d actually be doing.

The goal? To see how you think, problem-solve, and build solutions with both speed and depth.

We care about real-world impact, not just theoretical skills. If you can break down a complex problem and develop an effective solution, you’re exactly who we’re looking for.

Stage 3: Collaborative Problem-Solving

Real work doesn’t happen in isolation, and neither does our interview process. Once you receive your problem statement, we encourage open communication and collaboration.

Ask questions, discuss ideas, and refine your approach, just like you would on the job. This process gives you a real preview of how we work at Labellerr.

There are no surprises if you join our team because you've already experienced our problem-solving mindset, fast iteration, and teamwork firsthand.

A True Win-Win Approach

We designed our hiring process to be efficient and beneficial for both sides:

• Early stages: You invest minimal time and get quick feedback on whether there's a good fit.
• Later stages: We engage only with candidates who show strong mutual interest.
• Final stages: Only the most promising candidates spend time on real-world assignments.

This approach ensures you don’t waste time on unnecessary steps. If we’re not the right fit, you’ll know early and can focus on other opportunities.

But if we are, the later stages give you a real experience of what it’s like to work at Labellerr.

We don’t throw abstract puzzles at you. Instead, we present challenges that mirror the actual work you'd be doing, so you can showcase your problem-solving skills in real-world scenarios.

What Makes Us Different?

At Labellerr, we build tools that help AI teams get high-quality data for computer vision, generative AI, and intelligent agents. We’re a lean team where everyone, including the founders, plays multiple roles.

Here’s what makes us stand out:

• No traditional HR process(yet): You interact directly with the people you’ll work with.
• Every hire is crucial: We’re carefully building a strong founding team.
• Immediate impact: Your work matters from day one, with real, visible results.

We don’t believe in slow, bureaucratic hiring. We look for builders, problem solvers, and AI innovators who want to make an impact fast.

We're Experimenting. Your Input Matters.

Our hiring process is always evolving. We continuously improve it to find exceptional talent while making the experience better for candidates.

If you go through our process, we’d love to hear your feedback, what worked, what didn’t, and how we can make it better. Your insights will help shape how we hire future team members.

Is Labellerr Right for You?

Our hiring process benefits both sides. Even if you don’t join our team, you’ll gain:

• Hands-on experience solving real AI data quality challenges
• Insight into startup culture and how early-stage companies operate
• A reusable personal introduction you can use in future applications
• Practice collaborating on technical problems in a fast-moving environment

If you value efficiency, real-world challenges, and a transparent process, we’d love to hear from you.

If not, that’s okay too, not every company is the right fit for every candidate. But if you’re excited about pushing the boundaries of AI and working with a team that moves fast, we want to meet you.

Ready to Take the First Step?

Send us your comprehensive introduction and get ready to tackle a real-world challenge that reflects the actual work at hr@labellerr.com.

No wasted time, no pointless puzzles, just a clear and efficient process to identify exceptional talent.

At Labellerr, we’re not just hiring employees, we’re building a team of founding engineers who will shape the future of AI data quality.

If you're ready to make an impact, we’d love to hear from you.