Computer Vision Engineer

• 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
• We’re seeking a self-starter who enjoys hands-on work, thrives with occasional ambiguity, and can collaborate closely with cross-functional teams to translate customer and field needs into robust algorithms and measurable performance improvements.

• Experience 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

• 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

• Paid time off and holidays

• 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 )

Innovasea is an equal-opportunity employer.

All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.