Technical Recruiter, AI & Robotics

Posted 7 Days Ago
Be an Early Applicant
Toronto, ON, CAN
Hybrid
130K-150K Annually
Mid level
Artificial Intelligence • Computer Vision • Machine Learning • Robotics
The Role
Own full-cycle technical recruiting for engineering, machine learning, computer vision, robotics, and research roles. Responsibilities include specialized talent sourcing, market mapping, pipeline development, hiring-manager partnership, interview-process improvement, candidate engagement, offer closing, and recruiting analytics. The recruiter will build relationships across technical communities and help scale Mecka AI’s recruiting systems and practices.
Summary Generated by Built In
About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

Help us build the team building physical AI

Mecka is building the data engine that helps robots understand and operate in the physical world. That requires an extraordinary team spanning software, infrastructure, machine learning, computer vision, robotics and research.

We’re looking for a Technical Recruiter who can find those people—and convince them to build with us.

Reporting to our Director of Talent Acquisition, you’ll own technical searches from first outreach through to signed offer. You’ll work directly with hiring managers and company leaders, move with urgency, and help us build a lasting presence within the robotics and computer vision communities.

This is not a role for someone who waits for applicants. You’ll map specialized talent markets, develop relationships before there is an open role, and build pipelines that compound as Mecka grows.

What you’ll own
  • Lead full-cycle recruiting across engineering, ML, computer vision, robotics and other specialized technical roles

  • Find exceptional candidates through original research, targeted sourcing and long-term relationship building—not only LinkedIn searches and inbound applications

  • Partner with hiring managers to define the real need, sharpen the role and build an interview process that identifies it

  • Build trusted relationships across robotics and computer vision companies, research labs, universities and technical communities

  • Develop talent pipelines before roles open, particularly for specialized and hard-to-find profiles

  • Keep searches moving quickly while maintaining a high hiring bar and a strong candidate experience

  • Present and close offers, helping candidates understand Mecka’s technical ambition, ownership and upside

  • Use pipeline data and market intelligence to tell us where talent sits, what candidates care about and when our approach needs to change

  • Help improve the recruiting systems, tools and practices we’ll need as Mecka scales

What you bring
  • 4+ years of full-cycle technical recruiting experience . Must have some experience hiring specialized engineers, researchers or technical leaders in robotics, computer vision, physical AI, autonomous systems, ML or another deep-tech environment

  • Strong sourcing instincts and evidence that you can uncover people other recruiters miss

  • Experience operating at speed in a demanding startup, scaleup or similarly high-performance environment

  • The judgment to distinguish an impressive résumé from someone who will materially raise the bar

  • The credibility and curiosity to engage deeply technical candidates and hiring managers

  • Strong candidate-closing skills and comfort navigating compensation, equity and competing offers

  • High ownership: you identify obstacles, propose solutions and keep the process moving

Even better if you have
  • Existing relationships across robotics, computer vision or embodied-AI companies, labs and academic communities

  • Experience recruiting at the intersection of software, hardware and research

  • Familiarity with the talent emerging from conferences and communities such as CVPR, NeurIPS, CoRL, RSS or ICRA

  • Experience with Ashby and modern sourcing or talent-intelligence tools

Why Mecka

You’ll have direct access to the leaders making hiring decisions, ownership over some of our most important searches, and the opportunity to build a technical talent network—not simply fill requisitions.

The hiring bar is high. The pace is fast. The people you bring in will directly shape what Mecka becomes and we have super high ambitions. If you do too - you may be the perfect fit!

A Note on Applying

Studies show women and candidates from underrepresented groups often only apply when they meet 100% of the listed qualifications, while others apply after meeting 60%. If you don't check every box above but believe you can do the job, we encourage you to apply — we're looking for capability and trajectory, not a perfect checklist match.
Inclusive Hiring at Mecka

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Mecka regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.

Skills Required

  • 4+ years of full-cycle technical recruiting experience
  • Experience hiring specialized engineers, researchers, or technical leaders
  • Experience recruiting in robotics, computer vision, physical AI, autonomous systems, machine learning, or another deep-tech environment
  • Strong sourcing skills, including original research and targeted outreach
  • Experience working at speed in a demanding startup, scaleup, or high-performance environment
  • Strong candidate-closing skills and comfort navigating compensation, equity, and competing offers
  • Ability to engage credibly with technical candidates and hiring managers
  • Existing relationships across robotics, computer vision, embodied AI companies, labs, or academic communities
  • Experience recruiting across software, hardware, and research
  • Familiarity with CVPR, NeurIPS, CoRL, RSS, or ICRA communities
  • Experience with Ashby and modern sourcing or talent-intelligence tools
Am I A Good Fit?
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The Company
58 Employees
Year Founded: 2024

What We Do

Mecka AI is a data and infrastructure company that provides high-quality human movement data to accelerate the development of autonomous systems for humanoid robotics. It serves as the data and deployment layer for physical AI, capturing, structuring, and evaluating real-world activity to create labeled datasets that enable robots to learn and deploy reliably in commercial settings.

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