Computer Vision Engineer

2 weeks ago


Toronto, Ontario, Canada Project X Full time $120,000 - $180,000 per year

About Project X

Project X Ltd. drives success by focusing on building teams of incredibly talented and client-focused people, who love to problem solve and work on tough data problems. We reward hard work and forward-thinking with recognition and a supportive culture that celebrates success and wants to see you grow.

Our team members are trusted advisors to our clients and offer innovative solutions that solve complex data problems. Collaboration, creativity, data knowledge and experience run deep in our veins. We are passionate about building long-term relationships with our clients and staying true to our values. When adding new members to our team, we also look for people that are aligned to our values.

We are also passionate about our people. Hiring and developing people that seek challenges, like to jump in and learn new things, and are happy to lend a helping hand to a peer is what makes us successful.

We understand that it's our people that make us great.

Role Summary

You will develop end-to-end computer vision and deep learning solutions supported by scalable data pipelines and modern MLOps practices. The ideal candidate has hands-on experience with high-performance modeling in PyTorch or TensorFlow, deep knowledge of image similarity and localization methods, and comfort implementing production systems in GCP.

What You'll Do
  • Design, build, and deploy advanced computer vision and data engineering solutions on Google Cloud Platform.

  • Develop image similarity, object localization, and retrieval models using classical and deep learning techniques such as LoFTR, SuperGlue, D2-Net, and transformer-based architectures.

  • Train and fine-tune models on annotated datasets; implement training pipelines in PyTorch or TensorFlow with intelligent augmentation and validation methods.

  • Prototype and experiment in Google Colab with GPU/TPU acceleration integrated into GCP workflows.

  • Architect scalable ML and data pipelines using Vertex AI, Cloud Run, BigQuery, Dataflow, and Cloud Storage for both batch and streaming workloads.

  • Build ETL/ELT processes transforming raw image, video, and metadata into model-ready, high-quality datasets.

  • Containerize and deploy workloads using Docker, Cloud Build, and CI/CD pipelines while maintaining security, data protection, and reproducibility.

  • Implement feedback loops for continuous retraining and model improvement through automated annotation and metric evaluation.

  • Integrate and manage similarity search systems using FAISS, Milvus, or Pinecone for large-scale vector retrieval.

  • Expose inference and training services as APIs or microservices using FastAPI for scalable and real-time interactions.

  • Optimize GPU performance and reduce inference latency through pruning, quantization, and efficient batching strategies.

What You Bring
  • 4 years experience in computer vision, deep learning, or data engineering in production environments.

  • Advanced proficiency with Python, PyTorch or TensorFlow, and GCP (Vertex AI, BigQuery).

  • Proven success designing scalable data and ML pipelines.

  • Strong understanding of model training, deployment, and continuous improvement cycles.

  • Ability to collaborate across ML, DevOps, and backend engineering teams.

  • Curiosity, creativity, and attention to detail in experimental and production settings.

In our commitment to promote fair and equitable treatment of all employees and applicants, Project X Ltd. provides equal employment opportunities for all individuals regardless of age, sex, disability, race, ethnic origin, citizenship, creed, sexual orientation, marital status or any other ground as described in the Ontario Human Rights Code. In addition, accommodation will be provided during the hiring process.

Project X is an equal opportunity employer and welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.



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