About TRAICK AI
TRAICK AI is an innovative health-tech startup building AI-powered clinical decision support systems, with a strong focus on ultrasound, MRI-based early diagnostics. Our solutions are designed to empower clinicians with real-time, interpretable, and regulatory-compliant medical imaging analysis. As we expand our product line and scale globally, we’re seeking a Senior AI Engineer to lead our AI infrastructure and development efforts.
This is a strategic technical leadership role for an experienced professional passionate about building high-impact healthcare technologies. You will drive core AI development, optimize multi-modal learning pipelines, and play a central role in shaping our AI platform.
Key Responsibilities
- Architect, develop, and deploy production-grade AI models for medical image analysis (ultrasound, MRI)
- Lead research and development in segmentation, classification, multi-task learning applications
- Fine-tune and integrate large language models (LLMs) for clinical NLP tasks and decision support
- Drive model explainability (XAI) and regulatory-aligned transparency in clinical workflows
- Design robust CI / CD / CT / CM pipelines for scalable AI / ML infrastructure
- Lead MLOps initiatives including experiment tracking, automated training pipelines, and model versioning
- Collaborate with cross-functional teams (radiologists, software engineers, regulatory experts) to co-develop clinically impactful solutions
- Stay at the forefront of deep learning research and translate SOTA methods into practical, performant systems
Requirements
Qualifications
BSc in Computer Science, AI, Electrical Engineering, or a related field (MSc / PhD strongly preferred)5+ years of experience in deep learning, computer vision, or medical AIStrong proficiency in PyTorch and / or TensorFlowProven experience with architectures such as CNNs, Transformers, U-Net, EfficientNet, ViTsDeep understanding of model optimization : quantization, pruning, ONNX, TensorRTExperience with large-scale data pipelines, class imbalance handling, and metric-driven trainingProficient in Git, experiment tracking tools (e.g., Comet, MLflow), CI / CD automationAbility to lead technically while executing hands-on development when neededExcellent communication and collaborative skills in cross-disciplinary teamsPreferred Qualifications
Prior experience in medical imaging (ultrasound, MRI, CT) and real-world clinical deploymentKnowledge of privacy-preserving learning (e.g., federated learning) and edge inferenceFamiliarity with CE marking / FDA regulations for medical AI systemsStrong cloud infrastructure skills (AWS, SageMaker, Docker, Kubernetes, S3)Benefits
What We Offer
Opportunity to shape the future of AI in healthcare with measurable clinical impactA collaborative, research-driven team passionate about solving real-world challengesOwnership, autonomy, and leadership in a high-growth startup environmentCompetitive salary based on experienceAccess to academic collaborations, educational resources, and conference participation