2-3 years experience
Position Overview
We are looking for an AI/ML Engineer to join KlinIQ Ai’s data science & engineering team. The ideal candidate will work on developing and deploying AI models that support symptom triage, image analysis, virtual-doctor interactions, documentation automation, and remote monitoring workflows.
Key Responsibilities
- Design, implement and deploy machine learning and deep learning models (e.g., classification, segmentation, forecasting) for clinical/health-tech use cases
- Work on multimodal data (text, voice, images, sensor data) and integrate into scalable pipelines
- Collaborate with product, engineering and clinical teams to translate healthcare problems into data-driven solutions
- Perform data preprocessing, feature engineering, model training, validation, hyperparameter tuning and performance evaluation
- Deploy models to production (including monitoring, versioning, A/B testing and feedback loops)
- Ensure models meet regulatory, security, interpretability and compliance requirements (e.g., transparency of decision-support)
- Stay current with state-of-the-art research in AI, especially in healthcare/medical imaging/voice/NLP domains
Required Skills & Qualifications
- 0–2 years of AI/ML experience (or relevant internship/projects)
- Strong programming skills in Python (or other suitable languages) and familiarity with ML libraries/frameworks (TensorFlow, PyTorch, scikit-learn)
- Experience with data engineering: ETL, data pipelines, working with real-world (noisy) datasets
- Understanding of model evaluation metrics, overfitting, generalisation, cross validation
- Familiarity with at least one of text/NLP, voice/ASR, or image analysis
- Strong problem-solving, communication and teamwork skills
- Comfort working in a regulated domain (healthcare/clinical) and handling sensitive data
Nice-to-Have
- Experience with deploying models in production (Docker, Kubernetes, cloud)
- Knowledge of explainable AI (XAI), model interpretability and fairness
- Previous work in healthcare, med-tech, remote monitoring or triage systems
- Ability to work with real-time streams or embedded/edge systems
- Familiarity with SDKs for mobile/web integration of AI models