About CoLab
At CoLab, we help mechanical engineering teams bring life-changing products to market years sooner.
We build AI for engineers designing cars, medical devices, and jet engines. Products this complex aren't sketched and sent to production. Teams spend months on iterations, reviews, and tests, predicting how every part performs before anything is built. CoLab is where those reviews happen, and we capture the rationale behind every change. Other tools show what changed between versions. Only CoLab knows why. That's how our AI helps manufacturers like Bobcat, Triumph Motorcycles, and GE Appliances make better decisions, eliminate rework cycles, and get to market faster.
Proudly based in St. John’s, Newfoundland, CoLab started with one customer in 2018. Since then we’ve raised a $72M Series C, been named the 57th fastest growing company in North America by Deloitte (Fast 500™), signed multi-year AI partnerships with companies like Bombardier, and grown to a team of 250+.
About the Role
CoLab’s AutoReview product is a core part of how we bring AI and engineering expertise together to improve design quality. So far, much of that work has focused on 2D drawings. Now, we’re building the future of 3D AutoReview — and we need a backend engineer who’s excited to help in that mission.
You’ll join the AutoReview team and help build the systems that power intelligent 3D design analysis at scale. That includes everything from geometry parsing and model analysis to backend infrastructure, rule systems, and AI-assisted review workflows. This is deeply technical, multidisciplinary work that sits at the intersection of backend engineering, CAD systems, and machine learning.
You’ll spend time experimenting, testing assumptions, and solving problems that don’t have obvious answers. You won’t be handed perfectly scoped projects or detailed specs. But you will get ownership, support, and the opportunity to shape how AI-driven design review evolves inside some of the world’s leading engineering organizations.
Our Ideal Candidate
You’ve got solid backend engineering experience, ideally with exposure to 3D CAD modelling 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/401K matching and 100% health/dental coverage
- Fully remote within North America
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.
Skills Required
- 5+ years of backend development experience, ideally on a product or platform team
- Practical experience with 3D mathematics and graphics engines, CAD kernels, robotics, or 3D simulations
- Experience designing, developing, and maintaining robust, scalable backend systems and APIs
- Experience with SQL, NoSQL, and vector database storage paradigms
- Experience with ML, AI, or LLM concepts and productionization
- Familiarity with 3D model machine learning pipelines, including feature extraction, embeddings, model training, or inference
- Familiarity with agentic workflows such as pydantic-ai
- Experience integrating and prompting LLMs through APIs
- Knowledge of PyTorch, Hugging Face, or Scikit-learn
- Experience deploying machine learning services in cloud infrastructure such as AWS SageMaker or Amazon Bedrock
- Ability to work through ambiguous or loosely scoped technical challenges
- Excellent communication skills for translating technical problems into clear paths forward
- Experience with CAD modeling software such as SolidWorks, Creo, or Onshape
- Experience with mechanical engineering concepts
CoLab Software Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about CoLab Software and has not been reviewed or approved by CoLab Software.
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Affordable Benefits — Health and dental insurance are covered 100% for the employee, reducing out-of-pocket costs. Listings align with the stated package, indicating consistent core coverage across sources.
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Retirement Support — RRSP and 401(k) matching are explicitly included for Canada and the United States. This provides structured long-term savings support as part of the standard package.
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Leave & Time Off Breadth — Unlimited PTO covers vacation, personal, sick, and bereavement time. The breadth of leave options signals flexibility in time away from work.
CoLab Software Insights
What We Do
At CoLab, we help mechanical engineering teams bring life-changing products to market years sooner. CoLab is the AI platform for driving stronger engineering decisions. Every design review in CoLab builds a knowledge repository of design feedback, decisions, and lessons learned - which AI agents draw from to flag issues on future designs before they compound. The more your team works in CoLab, the smarter it gets and the faster you arrive at the ideal design. Companies like Ford, Komatsu, and Johnson Controls use CoLab to catch issues earlier, eliminate rework cycles, and bring products to market faster.
Why Work With Us
At CoLab, we work hard, celebrate wins together, and continuously strive to improve our craft. You'll be surrounded by driven, supportive teammates who are passionate about solving complex challenges for customers and building technology that helps some of the world's leading engineering teams collaborate and make better decisions.
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