Capture Platform Lead - System Architect

Mecka AI; Toronto; On-site; CAD 120,000 - 150,000; Full time

Job summary

Mecka AI, located in Toronto, Ontario, is looking for a Head of Hardware to lead the architecture of a high-quality capture platform. This hands-on leadership role requires driving product strategy from concept through mass production while ensuring quality and reliability.

The ideal candidate will have over 8 years of hardware engineering experience, with a track record of scaling consumer or wearable hardware. Experience in cross-functional team leadership and strong knowledge of embedded systems is essential.

Qualifications

• 8+ years in hardware engineering with experience shipping consumer or wearable hardware at volume.
• Broad systems engineering background deep in at least two areas: embedded/firmware, electrical, mechanical, or optics.
• Experience leading cross-functional hardware teams and working with contract manufacturers.

Responsibilities

• Lead the definition and convergence of capture device's sub-systems into a single platform.
• Set and own the quality and reliability standards for the device.
• Drive the product from prototype through mass production.

Skills

Embedded/firmware expertise

Electrical systems knowledge

Mechanical engineering

Optics engineering

Cross-functional team leadership

Quality assurance

Job description

About Mecka

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 and robotics teams. Our operations span multiple countries, with contributors, partners, and customers across North America and Asia.

Our Mission

Robotics will become the largest industry in human history — larger than anything that has come before it. As intelligent machines move into the physical world, they will dramatically expand global GDP, raise the material standard of living for everyone, and ultimately help make humanity a multiplanetary civilization. None of that happens without one thing: enormous amounts of high-quality, real-world data.

Mecka AI builds that foundation. We are the data infrastructure layer for robotics and embodied AI — the substrate that teaches machines to perceive, reason, and act in reality. Get this right, and we accelerate the most important technological transition of our time.

Our Culture

• Excellence as the baseline. We hold an extremely high bar and expect the best work of your career. Mediocrity isn't interesting to us.

• Highly technical. We reason from first principles, not by analogy. The best argument wins — regardless of title or tenure.

• Truth-seeking. We are relentlessly honest with ourselves and each other. We chase reality — measured, not assumed — and kill our own bad ideas fast.

• Maniacal urgency. The work matters and the clock is real. We move fast, ship, measure, and iterate.

• Extreme ownership. You own outcomes end-to-end — no hand-offs, no excuses, no waiting for permission.

• Hardcore. This is a high-intensity environment for people who want to do the defining work of their lives.

The role

As the company scales, building a reliable, high-quality capture platform is foundational to everything we do. As Head of Hardware, you lead the architecture and engineering of that platform and drive its strategy and roadmap from concept through mass production. You set the quality and reliability bar and lead the convergence of the electrical, firmware, mechanical, and optical sub-systems into one coherent product — the senior hardware authority for the company and the systems architect behind the device.

This is a hands‑on leadership role at an early stage. You'll build and grow the hardware engineering team, and partner across industrial design, software, supply chain, quality/reliability, and our China contract‑manufacturing partners to take the product from prototype through EVT/DVT/PVT to volume production. If you're energized by owning a wearable hardware platform from architecture through scaled production, this is that seat.

Responsibilities

• Lead the definition and convergence of the capture device's electrical, firmware, mechanical, and optical sub-systems into a single coherent platform, holding final technical authority on architectural trade-offs.

• Set and own the quality and reliability bar for a body‑worn device, and drive the test and design decisions that uphold it at scale.

• Drive the product from prototype through EVT/DVT/PVT to mass production, partnering closely with industrial design, supply chain, and our China manufacturing and reliability teams.

• Build, lead, and grow the hardware engineering team, and own the hiring roadmap behind it.

• Own the feedback loop that turns field and factory data into design improvements.

• Own the systems‑level reliability challenges unique to a body‑worn device — thermal, mechanical durability, connector and wear under all‑day motion — and set the engineering approach the team executes against.

Minimum qualifications

• 8+ years in hardware engineering with a track record of shipping consumer or wearable hardware at volume, including direct ownership of at least one full reliability ramp from prototype through mass production.

• Broad systems engineering background — deep in at least two of embedded/firmware, electrical, mechanical, and optics, and fluent enough to lead and evaluate the rest.

• Experience driving architecture convergence on complex consumer electronics and making cross‑disciplinary trade‑offs.

• Experience owning a hardware quality bar and a DVT/reliability process that caught issues before mass production.

• Experience leading cross‑functional hardware teams and working closely with contract manufacturers, ideally in China.

Preferred qualifications

• Experience with body‑worn or always‑on devices (action cameras, wearables, AR/VR, health/fitness).

• Background from a hardware org known for execution at scale (e.g. Meta Reality Labs, GoPro, DJI, Insta360, or a wearable startup that shipped in volume).

• Experience with camera/optics systems and on‑device compute, including ML workloads on edge hardware.