Computer Vision Engineer
Innovasea
full-time
Posted on:
Location Type: Hybrid
Location: Bedford • Canada
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About the role
- Lead the design, development, evaluation, and deployment of computer vision algorithms that power real-time perception and analytics in challenging underwater environments.
- Design and implement computer vision and deep learning algorithms for underwater applications (detection, tracking, segmentation, pose/key points, 3D reconstruction)
- Develop robust underwater image enhancement and domain adaptation approaches (color correction, dehazing, low-light, turbidity robustness)
- Create scalable training and evaluation pipelines: dataset curation, labeling workflows, augmentation, model training
- Define and track algorithm KPIs (accuracy, precision/recall, tracking stability, 3D error, latency, throughput) and run ablation studies to drive continuous improvement
- Optimize models for real-time deployment on edge hardware (Jetson / GPU): quantization, pruning, TensorRT , batching, pipeline profiling
- Collaborate with software/hardware teams to integrate models into production systems (APIs, streaming pipelines, monitoring, versioning, rollback strategies)
- Work with marine biology and ocean engineering stakeholders to ensure outputs support fish well-being, operational excellence, and scientific validity
- Travel domestically/internationally for R&D site work, system validation, and customer visits
Requirements
- Strong foundation in computer vision + deep learning: object detection, instance/semantic segmentation, multi-object tracking
- Proven experience building training/evaluation pipelines: dataset management, augmentation strategies, class imbalance handling , metrics design, test set hygiene, regression testing for models , experiment reproducibility and tracking
- Proficient in Python for ML development and C++ for production integration
- Hands-on experience with modern ML frameworks: PyTorch (preferred)
- Experience with deployment/optimization: TensorRT / ONNX, mixed precision, quantization , performance profiling, latency/throughput optimization
- Strong software engineering fundamentals: clean architecture, modular code, testing, CI/CD basics
- Git-based workflows, code review culture
- Excellent communication and collaboration across functions : ability to convert ambiguous problems into actionable experiments and deliverables
- Ability to maintain confidentiality and work in a fast-moving environment.
- Preferred / Nice-to-have
- Experience with underwater vision (turbidity, low-light, motion blur, color shift), domain adaptation, or robustness methods
- Experience with active learning, human-in-the-loop labeling, uncertainty estimation, drift detection
- Familiarity with MLOps tooling (Weights & Biases, MLflow , DVC, data lineage, model registry)
- Exposure to distributed training, multi-GPU, or cloud training workflows
Benefits
- Paid time off and holidays
- Employee Assistance Program
- Paid parental leave
- Pension
- Employer-paid medical, dental, vision
- Wellness Allowance
- Hybrid schedule option available ( must be locat ed in HRM and available to be onsite weekly )
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
computer visiondeep learningobject detectioninstance segmentationsemantic segmentationmulti-object trackingdataset managementmodel trainingPythonC++
Soft Skills
communicationcollaborationproblem-solvingconfidentialityadaptability