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Computer Vision Engineer, 3D

@ Mecka

Richmond Hill, Ontario

$200k–$230k/yrHybridFull-time5+ years experience
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Overview

Mecka is hiring a full-time Computer Vision Engineer, 3D to own the classical computer-vision side of its robotics data pipeline. The work covers 3D geometry, temporal filtering, inverse kinematics and delivery QA, with a focus on its 3D hands pipeline. The posting requires 5+ years of experience and strong Python skills, and it lists no salary, schedule or work arrangement.

Pay:

$200,000–$230,000 a year

Responsibilities:

  • Own multi-view geometry, calibration and reprojection
  • Design temporal filters that remove jitter
  • Run inverse kinematics and bone-length constraints
  • Build delivery QA metrics and visualizers
  • Support classical CV problems across the pipeline

Requirements summary:

  • 5+ years in software engineering and computer vision
  • Strong production Python; C++ a plus
  • Solid multi-view geometry and calibration
  • Temporal filtering and Kalman-family methods
  • Inverse kinematics on articulated structures
  • Working knowledge of pose and mesh regressors

Tools & skills

Source and dates

Employer career site / ATS feed · ashby

Employer posting date
2026-10-01
First seen by our source
2026-10-08
Source record updated
2026-10-20

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SenioritySenior
DepartmentSoftware development
Experience5+ years
Hours per week40 (estimated)
Work settingOffice
PositionMostly sitting
Physical demandsphysical low · computer high
LanguagesEnglish

Summary and details written by AI from the posting; the employer’s posting is the authority.

Mecka

Saved company profile

Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.

Data Layer for AI Robotics

Full company description

Mecka create large scale human data for AI and robotics training

LinkedIn followers
980
People associated on LinkedIn
38
Business categories
  • Robotics
  • Analytics
  • Artificial Intelligence (AI)
Other recorded names
  • Mecka
  • Mecka AI
Specialties
  • Robotics
  • Artificial Intelligence
  • and Data
Profile identifies a recruitment agency
No
Reported total investment
68,000,000

Currency and observation date were not supplied; this is not a current valuation or a funding round.

Mecka create large scale human data for AI and robotics training

FieldValue
IndustryData Infrastructure and Analytics
Company size2-10 employees
Organization typePrivately Held
SpecialtiesRoboticsArtificial Intelligenceand Data
Open jobs on Jobsy33
LinkedInView page
Job description

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.

The role

We're looking for a strong, coding-heavy computer vision engineer to own the classical side of our stack. Our models produce raw per-frame predictions; you own the traditional computer vision, temporal filtering, and inverse kinematics — backed by excellent software engineering — that turn those into clean, rigid, smooth, correctly-calibrated spatial data we can deliver.

You'll partner closely with our research teams — you need to understand the models, but you won't be training them.

Your immediate focus is our 3D hands pipeline, where this work is needed most today. From there you'll be our classical-CV specialist across the organization, brought in wherever geometry, filtering, or pipeline problems come up.

What You'll Do

  • Own the classical 3D geometry that places reconstructions correctly in space: multi-view geometry, triangulation, PnP, camera calibration, undistortion, and reprojection.

  • Design and tune temporal filters (low-pass, Kalman-family, interpolation) that remove jitter without losing real motion.

  • Run inverse kinematics and enforce physical constraints such as bone-length rigidity so reconstructed skeletons stay valid. Build the checks that keep bad frames out of delivery.

  • Turn model output into clean delivered data, including per-frame results, reports, and the QA metrics that gate delivery, and keep the pipeline running at scale.

  • Build visualizers and dashboards to inspect trajectories, overlays, and failure cases.

  • Be the go-to engineer for classical computer-vision problems across the pipeline as they come up.

  • go-to for classical computer-vision problems elsewhere in the pipeline as they come up.

What You Bring
Must-have:

  • 5+ years of professional experience in software engineering and computer vision.

  • Strong software engineering. This is a coding-heavy role: clean, efficient, production Python (C++ is a plus).

  • Solid multi-view geometry: triangulation, PnP, camera calibration, reprojection, and coordinate transforms.

  • Temporal filtering and signal processing: low-pass and Kalman-family filters, interpolation, and a feel for the trade-off between smoothness and fidelity.

  • Inverse kinematics and rigid-body or bone-length constraints on articulated structures.

  • Enough ML to work with deep models such as pose and mesh regressors, including their outputs and failure modes, without training them yourself.

  • A data-quality mindset: comfortable with noisy real-world data and building QA that catches problems before customers do.

Nice-to-have:

  • Human pose or mesh reconstruction (hand or body), including keypoint and mesh pipelines.

  • Depth in Bayesian filtering or state estimation; experience with optimization frameworks such as Ceres or GTSAM.

  • Building CV tooling such as trajectory visualizers and overlay or QA dashboards.

  • Stereo, multi-view, or ego-exo capture experience.

  • Light temporal ML, such as small networks for smoothing or gap-filling.

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.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs.

We may use AI-assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.

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