Senior AI Engineer

About TRAICK AI

TRAICK AI is an innovative health-tech startup building AI-powered clinical decision support systems, with a strong focus on ultrasound-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.

Key Responsibilities

• Architect, develop, and deploy production-grade AI models for medical image analysis (ultrasound)
• Lead research and development in segmentation, classification, multi-task learning applications and image processing
• 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

Qualifications

• BSc in Computer Science, AI, Biomedical Engineering, or a related field (MSc/PhD strongly preferred)
• 5+ years of experience in deep learning, computer vision, or medical AI
• Fluent in Turkish and English
• Strong proficiency in PyTorch and/or TensorFlow
• Proven experience with architectures such as CNNs, Transformers, U-Net, EfficientNet, ViTs
• Deep understanding of model optimization: quantization, pruning, ONNX, TensorRT
• Experience with large-scale data pipelines, class imbalance handling, and metric-driven training
• Proficient in Git, experiment tracking tools (e.g., Comet, MLflow), CI/CD automation
• Ability to lead technically while executing hands-on development when needed
• Excellent communication and collaborative skills in cross-disciplinary teams

Preferred Qualifications

• Prior experience in medical imaging (ultrasound) and real-world clinical deployment
• Knowledge of privacy-preserving learning (e.g., federated learning) and edge inference
• Familiarity with CE marking / FDA regulations for medical AI systems
• Strong cloud infrastructure skills (AWS, SageMaker, Docker, Kubernetes, S3)
• Fluent in Turkish and English, enabling seamless collaboration in international and multidisciplinary research and regulatory environments.

What We Offer

• Opportunity to shape the future of AI in healthcare with measurable clinical impact
• A collaborative, research-driven team passionate about solving real-world challenges
• Ownership, autonomy, and leadership in a high-growth startup environment
• Access to academic collaborations, educational resources, and conference participation