MLOps Engineer
At a glance
Mid-level ML Platform & Ops role at planitar. Waterloo · full-time · no salary stated · we estimate CA$122,100–CA$139,500 across Canada.
planitar has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build a scoring system for each new model and block releases when evaluations reveal regressions
- Automate and track versions for the data-generation and model-training workflows
- Set up experiment records and a central registry for trained models
- Package models for the drafting desktop app and automated pipeline, with separate rollout and rollback controls
- Track production model quality, drift, cost and latency while managing GPU compute and ML delivery pipelines
What you bring
- At least four years in MLOps, ML platforms or ML-focused software engineering, including models you brought into production
- Strong Python skills, the ability to work in C++ codebases, and experience with PyTorch training and ONNX export
- Hands-on knowledge of experiment tracking, model registries, data versioning, Docker, workflow orchestration and CI/CD
- Experience with AWS and Linux systems using GPUs
Who this fits
This mid-level role suits someone ready to be the first and sole owner of the ML platform on a small research team. The work spans model infrastructure from training and evaluation through deployment and production monitoring. The position is based in Waterloo, Canada, with a hybrid work environment.
From the employer
ABOUT US
At Planitar, we build technology that helps people see and understand the world’s spaces more clearly.
We are the creators of iGUIDE, a powerful property technology solution that combines immersive 3D tours, accurate floor plans and reliable spatial data into a single, easy-to-use system. Our cameras and software platform are used by professionals in real estate, insurance, construction and property management to simplify their work and deliver better results.
Planitar recently joined REA Group, one of the world’s leading digital property companies. REA operates Australia’s largest residential and commercial property platforms, including realestate.com.au and has a growing global footprint across Asia and North America. Together, we are shaping the future of property technology, combining Planitar’s deep spatial data expertise with REA’s global scale and innovation engine.
OUR VISION
A connected future where reliable spatial data enables informed decisions across the property lifecycle.
OUR VALUES
- Integrity: We do the right thing even when it’s hard.
- Teamwork: We are one team, on a big mission.
- Innovation: We value creative solutions for emerging opportunities.
- Accountability: We honour our commitments.
ABOUT THE ROLE
Planitar's Advanced Research Group builds the AI that turns 360° scans into floor plans. We are hiring our first MLOps Engineer to build the infrastructure that trains, evaluates, deploys and monitors our floor-plan generation and automated drafting QA models. You will own this platform end to end.
RESPONSIBILITIES
- Build an automated evaluation harness that scores every new model and gates releases on
regressions. - Automate and version the data generation and training pipelines.
- Set up experiment tracking and a model registry.
- Package and deploy models into our desktop drafting application and automated pipeline, with independent rollout and rollback.
- Operate LLM-based agents in production: prompt and model versioning, cost and latency tracking.
- Monitor model quality, drift and cost in production.
- Manage our GPU compute and CI/CD for ML.
QUALIFICATIONS
- 4+ years in MLOps, ML platform or ML-focused software engineering, with models you took to production.
- Strong Python; able to work with C++ codebases.
- PyTorch training workflows and ONNX export.
- Experiment tracking, model registries and data versioning (e.g. MLflow, W&B, DVC).
- Docker, workflow orchestration and CI/CD.
- AWS and Linux GPU environments.
- Comfortable as the sole owner of a platform on a small research team.
NICE TO HAVE
- LLMOps or agent evaluation experience.
- Computer vision, 360° imagery or point-cloud data.
- Shipping ML inside desktop or edge applications.
PERKS AND BENEFITS
- 100% employer-paid flexible benefits plan
- Comprehensive Health & Dental coverage
- Health Spending Account (HSA) or Lifestyle Spending Account (LSA) options
- 3% DPSP match
- Hybrid Work Environment
- Professional Development Incentive
- Opportunities to grow as we scale
- The backing of a global industry leader through REA Group
ACCESSIBILITY, INCLUSION & AI DISCLOSURE
Planitar is committed to a diverse, equitable, inclusive workplace and welcomes applications from all backgrounds. This is a back fill position. We provide accommodation under AODA at any hiring stage upon request. In line with Ontario law, we use AI only to summarize interview notes, never to screen, assess, or decide on candidates — all decisions are made by our team. Please note this is a new position.