At CoLab, we want to help mechanical engineering teams bring life-changing products to market years sooner.
CoLab is a cloud based platform for engineering design review. We make it easy for subject matter experts (SMEs) across your business to access, evaluate, and comment on 2D drawings and 3D models. Our built-in AI peer checker, AutoReview, scans designs for common errors or non-compliance with your standards and guidelines. AutoReview creates markups and comments on your files, in context – just like a human checker.
With CoLab, human SMEs and AI work together to help you make better decisions and improve designs faster. We automatically capture knowledge from across your global business that would otherwise be buried in emails, spreadsheets, slide decks, and unknown locations in Sharepoint or PLM. Then, we make sure every lesson learned and every design guideline is applied exactly when it matters.
Companies like Johnson Controls, Komatsu, Schaeffler, and Polaris have launched products 40% faster, cut BOM costs by 50%, and reduced quality escapes by 15% in 1 year.
About the Role
CoLab’s AutoReview is a cornerstone of how we bring AI and human expertise together for design quality. So far, most of that work has focused on 2D. Now, we’re building the future of 3D AutoReview—and we need a backend engineer who’s excited to help us invent it.
You’ll be the technical driver for 3D AutoReview inside our Scale team, helping take responsibility for everything from geometry parsing and model analysis to pipeline ownership. It’s deeply technical, multidisciplinary work—mixing backend engineering, mechanical design knowledge, and experimental problem-solving. There’s no playbook for this, so if you love being the first to figure it out, you’ll thrive here.
You won’t be handed a perfect spec. But you will be given ownership, support, and room to try (and fail) on your way to building something that hasn’t been built before.
Our Ideal Candidate
You’ve got solid backend engineering experience, ideally with exposure to 3D CAD modeling or using tools like OpenCascade or Parasolid. You’re comfortable with math-heavy problems (linear algebra, vector calculus), and bonus points if you’ve worked in ML/LLM environments or with HOOPS.
You like to understand the “why” behind the work and communicate it clearly. You thrive in ambiguity and don’t wait for someone else to go first. If something’s unclear, you figure it out—and then explain it to the rest of the team. You’re ready to be the go-to person for 3D anomalous within the AutoReview space and help others get up to speed.
Job Responsibilities
- Become a key contributor in the backend development for 3D AutoReview features, from pipeline architecture to production delivery
- Experiment with geometry parsing, quality detection, and context generation for 3D model review
- Partner with backend, frontend, and product teams to drive the delivery of high-impact features with speed, quality, and cross-functional alignment.
- Collaborate with ML teams to incorporate intelligence into the 3D review process
- Develop extensible systems for custom rule creation and reference data in 3D AutoReview
- Help set and maintain high technical standards across the team
Qualifications
- 5+ years of experience in backend development, ideally in a product or platform team
- Solid grasp of 3D math with practical experience in graphics engines, CAD kernels (HOOPS, OpenCascade, Parasolid), Robotics, 3D simulations, etc.
- Hands-on experience designing, developing, and maintaining robust, scalable backend systems and APIs
- Experience working with multiple data storage paradigms (SQL, NoSQL, and vector databases)
- Experience with ML/AI/LLM concepts and productionalization
- Familiarity with 3D model ML pipelines (e.g., feature extraction, embedding generation, model training, or inference)
- Familiarity with agentic workflows (e.g., pydantic-ai)
- Experience integrating and prompting large language models (LLMs) via APIs (e.g., OpenAI, Anthropic, Google Gemini)
- Knowledge of ML frameworks such as PyTorch, Hugging Face, or Scikit-learn
- Experience deploying ML services in cloud infrastructure (e.g., AWS SageMaker, Amazon Bedrock, etc.)
- Comfortable working with ambiguous or loosely scoped technical challenges
- Excellent communicator—able to translate technical problems into clear paths forward
- Experience with CAD modeling software like SolidWorks, Creo, or OnShape is a strong plus
- Experience with mechanical engineering concepts is a strong plus
Extra Details
- This is a full-time, permanent position with a competitive compensation package that includes stock options
- Includes extended health benefits, unlimited paid vacation, and RRSP matching and 100% health/dental coverage
- Fully remote within Canada
Equity Note
Frequently cited statistics show that people who identify with historically marginalized groups are likely to apply to jobs only if they meet 100% of the qualifications. We encourage you to help us break that statistic and apply even if you don’t meet every single qualification—your potential is what matters most to us.
