Job Title: Machine Learning Engineer (Computer Vision)
Location: Toronto (Hybrid – 1 day/week after onboarding)
Employment Type: Contract 6 Months
Pay Rate: $75/h on Inc
Role Overview
We are seeking an experienced Machine Learning Engineer to design, optimize, and deploy computer vision models for large-scale, real-time edge inference. This role will own the end-to-end ML lifecycle, including model development, MLOps automation, cloud deployment, and edge optimization.
Key Responsibilities
Design, train, fine-tune, and evaluate computer vision and object detection models
Develop and optimize MLOps pipelines using Vertex AI and Kubeflow Pipelines (KFP)
Convert and optimize models for edge deployment using TensorFlow Lite (TFLite), including quantization and hardware acceleration
Build automated validation and deployment workflows to ensure model quality
Manage model versioning and deployment artifacts in Google Cloud Storage (GCS)
Collaborate with engineering teams to deliver scalable AI solutions
Required Skills
4+ years of experience in Machine Learning Engineering
Strong experience with Computer Vision, CNNs, and Object Detection
Deep expertise in TensorFlow and/or PyTorch
Hands-on experience with Vertex AI, Kubeflow Pipelines (KFP), and GCP
Experience optimizing models using TFLite
Strong Python programming skills
Experience with Docker and cloud-native deployments
Strong problem-solving and software engineering fundamentals
Nice to Have
Experience with YOLOv8 (Ultralytics)
Google Cloud Composer (Airflow)
Dataflow / Apache Beam
CI/CD for ML pipelines
Generative AI, RAG, or Multi-Agent systems
What We're Looking For
Strong hands-on ML engineer with production deployment experience
Expertise in building scalable AI solutions on GCP
Experience deploying models to edge devices
Ability to work independently in a fast-paced environment
Work Arrangement
Hybrid model
Initial onboarding: 1–3 days/week onsite
Long-term expectation: approximately 1 day/week onsite
Ability to travel to Toronto office monthly if required
Occasional after-hours support for deployments and upgrades

Machine Learning Engineer

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